Explore 6 python data engineer jobs from 2 hiring companies in Smith, NV, US. Filter by remote, salary, experience, and company, then open any listing to apply.

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Python Data Engineer Jobs

Socure

Broadcom

Remote

Onsite

<h2>Why Socure?</h2>Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.<div><div style="left:0;width:100%;height:0;position:relative;padding-bottom:56.338%"><iframe src="https://embedded-media.ashbyhq.com/embed/f47d1f69-9ec3-4b39-a4ac-f777b1c17492/868e13ef-833e-4d43-8789-7af398acc5d8" style="top:0;left:0;width:100%;height:100%;position:absolute;border:0" allowfullscreen scrolling="no" allow="encrypted-media *; picture-in-picture *;" sandbox="allow-scripts allow-same-origin allow-presentation"></iframe></div></div><h2>About the Role</h2>We are looking for a Senior Data Engineer to join our Data Automation team. You will play a critical role in designing and building scalable data platforms and pipelines that power Socure’s identity verification products and analytics. This role is ideal for someone who has a strong passion for solving real business problems with data, and combines deep hands-on data engineering expertise with strong ownership. <h2>What You'll Do</h2>• Design and build batch and streaming data pipelines to support automated data ingestion, ML feature engineering and analytics across multiple product domains.• Own end-to-end delivery of complex, ambiguous data initiatives, including architecture, implementation, testing, deployment, monitoring, and documentation.• Develop and evolve the data platform to support large-scale data processing using modern cloud-native technologies.• Automate data operations (validation, quality checks, alerting, backfills, and recovery workflows) to reduce manual effort and improve consistency.• Optimize cost, performance, and reliability of data workloads.• Partner closely with cross-functional teams (Data Science, Product, Engineering) to understand requirements, translate them into technical solutions.• Evaluate and adopt new technologies (new processing engines, storage formats, orchestration tools, GenAI-assisted ingestion) to keep the platform modern and efficient. <h2>What You Bring</h2>• 5+ years of hands-on data engineering experience, building and maintaining production-grade data platforms and pipelines.• Strong programming skills in general-purpose language (such as Python or Scala) for data processing, and SQL for data analytics.• Deep experience with distributed data processing frameworks, such as Apache Spark, including performance tuning and optimization.• Proven experience building data solutions using services on AWS (EMR, Lambda, s3, etc).• Strong understanding of data modeling and data warehousing concepts, including partitioning, schema design for large-scale datasets.• Experience operating and supporting production pipelines, including monitoring, alerting, incident response, and improving reliability over time.• Solid foundation in software engineering practices, including version control, CI/CD, testing strategies, and code review.• Strong communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.Preferred Qualifications• Experience with streaming or near-real-time data processing (Kafka, Kinesis, etc).• Hands-on experience with data orchestration tools (Airflow, Step Functions, etc).• Familiarity with modern data platform patterns such as Data Lakehouse, Data Mesh, and large-scale data sharing across teams.• Experience with prompt engineering using modern GenAI, Large Language Models (LLM).• Experience mentoring other engineers and contributing to engineering-wide standards, best practices.As a note; Socure cannot provide sponsorship now or in the future for this role.Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us!<a target="_blank" rel="noopener" href="https://www.youtube.com/c/Socure">YouTube</a> | <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/company/socure/">LinkedIn</a> | <a target="_blank" rel="noopener" href="https://x.com/socureme">X (Twitter)</a> | <a target="_blank" rel="noopener" href="https://www.facebook.com/socure/">Facebook</a>

Senior Data Engineer

5+ years of hands-on data engineering; Python/Scala; SQL; Spark; AWS (EMR, Lambda, S3); data modeling; production pipelines; monitoring; collaboration.

<h2>Why Socure?</h2>Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.<div><div style="left:0;width:100%;height:0;position:relative;padding-bottom:56.338%"><iframe src="https://embedded-media.ashbyhq.com/embed/f47d1f69-9ec3-4b39-a4ac-f777b1c17492/868e13ef-833e-4d43-8789-7af398acc5d8" style="top:0;left:0;width:100%;height:100%;position:absolute;border:0" allowfullscreen scrolling="no" allow="encrypted-media *; picture-in-picture *;" sandbox="allow-scripts allow-same-origin allow-presentation"></iframe></div></div><h2>About the Role</h2>Socure is the leading provider of digital identity verification and fraud prevention solutions, leveraging AI and machine learning to power the most accurate decisions. Our mission is to eliminate identity fraud and ensure online trust across industries.As a Staff Data Scientist for RiskOS, you will sit at the intersection of platform data science, fraud and risk analytics, and Generative AI. You will own end‑to‑end development of data‑driven solutions on the RiskOS platform—from heavy‑duty data exploration and cleaning, through modeling and GenAI agent design, all the way to production deployment and monitoring.You will leverage your expertise in fraud and risk management to help develop and integrate robust detection and decisioning models, and your experience with Generative AI to design, evaluate, and operationalize LLM‑powered tools that improve analytics, workflows, and case investigations.You will collaborate closely with engineering and platform teams to build scalable, production‑grade pipelines and services, and with product and risk leaders to ensure RiskOS delivers actionable insights, self‑serve analytics, and best‑in‑class fraud prevention at scale.This is a highly collaborative, hands‑on technical leadership role for someone who enjoys owning complex data problems end‑to‑end and acting as a force multiplier for other data scientists and product teams. <h2>What You'll Do</h2><ul style="min-height:1.5em"><li>Develop and implement advanced analytics on top of noisy, heterogeneous RiskOS data to understand user behavior, product usage, fraud patterns, and workflow effectiveness; translate findings into concrete product and risk strategy improvements.</li><li>Architect and build scalable data pipelines and production ML workflows, collaborating with data engineering to ensure robust, reliable, and efficient data processing for both batch and streaming use cases.</li><li>Lead the design, execution, and analysis of experimentation frameworks to optimize user journeys, feature adoption, and workflow performance across the RiskOS platform.</li><li>Lead the creation and evaluation of Generative AI solutions (LLMs, agents, prompt‑based tools) that automate analytics, power case review and investigation assistants, streamline documentation, and enhance RiskOS workflows and reporting.</li><li>Define rigorous evaluation frameworks for GenAI solutions, including offline benchmarks, human‑in‑the‑loop review, safety and hallucination checks, and impact measurement in production.</li><li>Partner with platform and engineering teams to define and build core RiskOS data science infrastructure, including feature stores, model‑serving APIs, evaluation services, and monitoring frameworks for both traditional ML and GenAI systems.</li><li>Own end‑to‑end deployment of production‑grade solutions: packaging models and GenAI workflows, integrating with RiskOS services, establishing SLAs, and instrumenting telemetry, alerting, and feedback loops.</li><li>Develop and automate tools for model evaluation, stress testing, backtesting, and adversarial scenario simulation to ensure robustness and operational resilience—especially in high‑risk fraud and compliance contexts.</li><li>Enable product and risk teams through self‑serve analytics and tools: build dashboards, template analyses, and GenAI‑driven assistants that help non‑technical users explore RiskOS data, tune workflows, and debug decisions.</li><li>Collaborate cross‑functionally with product, engineering, risk, solution consulting, and customer‑facing teams to translate business requirements into data‑driven solutions and actionable insights, particularly for fraud and risk use cases on RiskOS.</li><li>Mentor and provide technical guidance to other data scientists and analysts, modeling best practices in experimentation, software engineering hygiene, GenAI safety, and rigorous model evaluation.</li><li>Ensure all solutions adhere to best practices in data privacy, security, and compliance, especially when handling sensitive PII and financial data in regulated fintech and public‑sector environments.</li><li>Contribute to company‑wide standards for ML and GenAI explainability, risk evaluation, feature logging, and documentation, helping raise the overall AI bar across Socure.</li><li>Communicate complex technical concepts and findings clearly to both technical and non‑technical stakeholders, including executive leadership and external partners.</li></ul><h2> What You Bring</h2><ul style="min-height:1.5em"><li>Master’s or PhD in Computer Science, Machine Learning, Statistics, Engineering, or a related quantitative field, or equivalent professional experience.</li><li>6+ years of hands‑on experience in data science, machine learning, or high‑scale data engineering roles, with a proven track record in fraud prevention, risk analytics, or complex decisioning systems.</li><li>Strong experience applying Generative AI in production or near‑production contexts, including:</li><li>Building and evaluating LLM‑based applications or agents (e.g., retrieval‑augmented generation, workflow assistants, data‑insight copilots).</li><li>Prompt design and optimization, safety and guardrail techniques, and quantitative/qualitative evaluation of LLM outputs.</li><li>Deep proficiency in Python and SQL, with hands‑on experience using ML frameworks such as scikit‑learn, XGBoost, TensorFlow, or PyTorch, plus modern GenAI/LLM tooling (e.g., OpenAI/Anthropic APIs, Hugging Face ecosystems, orchestration frameworks).</li><li>Demonstrated experience building and maintaining scalable data pipelines and deploying ML models in production environments, ideally involving streaming or near‑real‑time data and modern data platforms (e.g., Databricks, Spark, PySpark, BigQuery, or similar).</li><li>Solid understanding of data engineering concepts, including ETL, data warehousing, schema design, and distributed computing.</li><li>Experience with platform‑oriented data science: working with feature stores, model‑serving infrastructure, CI/CD for ML, automated monitoring, and feedback collection workflows.</li><li>Hands‑on experience wrangling messy, high‑volume datasets: designing robust cleaning, normalization, and quality‑control processes; reasoning under missing or biased data; and building reusable data abstractions for other users.</li><li>Familiarity with privacy‑preserving ML techniques, secure data handling, and regulatory requirements in fintech, credit, or public‑sector environments is strongly preferred.</li><li>Proven ability to collaborate effectively in cross‑functional, fast‑paced teams; strong communication skills with comfort presenting trade‑offs and recommendations to senior stakeholders.</li><li>Product‑minded and outcome‑oriented: you care about how models and GenAI tools are used, how they shape user experience and risk posture, and how to measure their real‑world impact.</li></ul><h3>Preferred Qualifications</h3><ul style="min-height:1.5em"><li>Direct experience with fraud/risk modeling, identity verification, or trust &amp; safety.</li><li>Prior work on orchestration platforms, case‑management tools, or rules/decision engines.</li><li>Experience mentoring senior ICs and setting technical direction for a small data science group.</li></ul>Please note that we are unable to provide sponsorship for this role; now or in the future. Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us!<a target="_blank" rel="noopener" href="https://www.youtube.com/c/Socure">YouTube</a> | <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/company/socure/">LinkedIn</a> | <a target="_blank" rel="noopener" href="https://x.com/socureme">X (Twitter)</a> | <a target="_blank" rel="noopener" href="https://www.facebook.com/socure/">Facebook</a>

Staff Data Scientist - RiskOS

Data Scientist

6+ years in data science or high-scale data engineering; strong GenAI experience; production ML; fraud/risk knowledge; cross-functional collaboration.

<h2>Why Socure?</h2>Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.<div><div style="left:0;width:100%;height:0;position:relative;padding-bottom:56.338%"><iframe src="https://embedded-media.ashbyhq.com/embed/f47d1f69-9ec3-4b39-a4ac-f777b1c17492/868e13ef-833e-4d43-8789-7af398acc5d8" style="top:0;left:0;width:100%;height:100%;position:absolute;border:0" allowfullscreen scrolling="no" allow="encrypted-media *; picture-in-picture *;" sandbox="allow-scripts allow-same-origin allow-presentation"></iframe></div></div><h2>About the Role</h2>As a Data Scientist II at Socure, you will occupy a high-impact, "bridge" role between our core Watchlist R&amp;D and the Data Science Customer Applications (DSCA) teams. Your mission is to accelerate the transition from model development to real-world deployment by building the automated analysis frameworks and monitoring systems that drive customer success. You won’t just build models; you will create the technical connective tissue—including high-performance pipelines and custom dashboards—that allows Socure to onboard clients faster, resolve complex issues effectively, and continuously improve our models through a closed-loop feedback system.<h2>What You'll Do</h2><ul style="min-height:1.5em"><li>Develop Analysis Frameworks: Design and maintain scalable frameworks that allow the DSCA team to perform fast, effective client resolutions during POCs, onboarding, and for existing production customers.</li><li>Bridge R&amp;D and Operations: Act as the primary technical liaison between Watchlist DS and DSCA, translating complex model behaviors into actionable insights for customer-facing teams.</li><li>Build Monitoring &amp; Alerting Systems: Create and manage mission-critical dashboards and real-time alert systems to monitor model performance, identify drift, and surface false positives/negatives at a sub-segment level.</li><li>Drive Closed-Loop Model Improvement: Systematically monitor customer production data and POC findings to integrate real-world feedback back into the core model development cycle.</li><li>Enhance In-House Pipelines: Build and optimize end-to-end data pipelines (using Spark and Airflow) that support custom reporting and automated performance tracking for Watchlist POCs.</li><li>Collaborate Cross-Functionally: Work closely with Product, Engineering, and Compliance to translate customer needs and regulatory requirements into measurable machine-learning objectives.</li></ul><h2>What You Bring</h2><ul style="min-height:1.5em"><li>Education: Bachelor’s degree in a quantitative field (Computer Science, Statistics, Mathematics, or similar) with 3–5 years of experience —or— a Master’s/Ph.D. with 1–3 years of experience.</li><li>Technical Proficiency: Strong programming skills in Python and SQL, with hands-on experience in Spark and Databricks.</li><li>Pipeline &amp; Infrastructure: Experience with Airflow for orchestration and a working knowledge of Infrastructure as Code (e.g., Terraform) and AWS environments.</li><li>Analytical Rigor: Solid grasp of descriptive statistics, hypothesis testing, and model evaluation metrics (Precision, Recall, F-beta, ROC-AUC).</li><li>ML &amp; Data Engineering: Practical experience in data curation, labeling strategies, and building automated data-quality validation checks.</li><li>Communication &amp; Impact: Excellent ability to communicate complex technical findings to both R&amp;D peers and non-technical stakeholders.</li><li>Passion for the Domain: A strong interest in NLP, LLMs, and staying ahead of the curve in compliance and regulatory technology.</li></ul><h3>Preferred Qualifications</h3><ul style="min-height:1.5em"><li>Experience with Elasticsearch and real-time data indexing.</li><li>Background in AML (Anti-Money Laundering), Sanctions Screening, or Identity Fraud prevention.</li><li>Prior experience in a "Customer Data Science" or "Solutions DS" role where you built tools for internal or external stakeholders.</li></ul>Please note that sponsorship is not available at this time.Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us!<a target="_blank" rel="noopener" href="https://www.youtube.com/c/Socure">YouTube</a> | <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/company/socure/">LinkedIn</a> | <a target="_blank" rel="noopener" href="https://x.com/socureme">X (Twitter)</a> | <a target="_blank" rel="noopener" href="https://www.facebook.com/socure/">Facebook</a>

Data Scientist II - Global Watchlist 

Data Scientist II

Bachelor’s in a quantitative field with 3–5 years experience, or Master’s/PhD with 1–3 years; strong Python and SQL; experience with Spark and Databricks; Airflow; Terraform; AWS; solid statistics and ML/data engineering skills; good communication; interest in NLP and compliance tech.

<h2>Why Socure?</h2>Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.<div><div style="left:0;width:100%;height:0;position:relative;padding-bottom:56.338%"><iframe src="https://embedded-media.ashbyhq.com/embed/f47d1f69-9ec3-4b39-a4ac-f777b1c17492/868e13ef-833e-4d43-8789-7af398acc5d8" style="top:0;left:0;width:100%;height:100%;position:absolute;border:0" allowfullscreen scrolling="no" allow="encrypted-media *; picture-in-picture *;" sandbox="allow-scripts allow-same-origin allow-presentation"></iframe></div></div><h2>About the Role</h2>Socure is looking for Software Engineering Interns to join the RiskOS team for a hands-on summer internship. RiskOS is Socure's real-time risk decisioning platform — used by financial institutions for identity verification, fraud detection, and compliance workflows. This role is for current master's students who want to build strong engineering skills while working on AI agents, data reporting pipelines, and product features that serve real customers.During the internship, you will work alongside experienced engineers on projects spanning AI agent development, analytics infrastructure, and full-stack product work.<h2>What You’ll Do</h2><ul style="min-height:1.5em"><li>Work with senior engineers to design, build, test, and ship product features across backend and frontend.</li><li>Write clean, readable, and well-tested code that follows team standards and code review practices.</li><li>Build and extend AI agents that power RiskOS.</li><li>Contribute to data reporting and analytics infrastructure — build parameterized report templates, extend the real-time analytics pipeline, and improve embedded dashboards.</li><li>Support backend development including APIs, data processing, and internal tools in Go.</li><li>Learn how software runs in production, including containers, CI/CD, cloud environments, monitoring, and logging.</li><li>Take part in agile team activities such as standups, sprint planning, and retrospectives.</li><li>Document designs, technical decisions, and usage notes so other engineers can build on your work.</li><li>Own a clearly scoped internship project from design to handoff by the end of the program. </li></ul><h2>What You Bring</h2>Education<ul style="min-height:1.5em"><li>Currently enrolled in a Master's degree program in Computer Science, Computer Engineering, or a related technical field.</li><li>Internship is intended for active students whose studies align with the work.</li></ul>Preferred Experience<ul style="min-height:1.5em"><li>Prior software development experience through a full-time role, internship, or similar hands-on work.</li><li>Coursework or project experience in any of: AI/ML systems, LLM applications, data engineering, or distributed systems.</li></ul>Technical Fundamentals<ul style="min-height:1.5em"><li>Strong understanding of data structures, algorithms, complexity, and basic system design.</li><li>Basic understanding of backend services, APIs, databases, queues, and how web applications work end to end.</li><li>Basic understanding of frontend fundamentals and at least one modern framework such as React, Angular, or Vue.</li><li>Basic understanding of servers, cloud environments, containers, and monitoring and logging concepts.</li><li>Basic proficiency in at least one backend programming language such as Go, Java, or Python.</li><li>Familiarity with Git and common software development workflows.</li></ul>Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us!<a target="_blank" rel="noopener" href="https://www.youtube.com/c/Socure">YouTube</a> | <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/company/socure/">LinkedIn</a> | <a target="_blank" rel="noopener" href="https://x.com/socureme">X (Twitter)</a> | <a target="_blank" rel="noopener" href="https://www.facebook.com/socure/">Facebook</a>

Engineering Intern- AI Agents, Data & RiskOS

Engineering Intern

Master's student in computer science/engineering; active enrollment; internship aligned with studies; software development experience; knowledge of AI/ML, data engineering, or distributed systems preferred.

Please Note:1. If you are a first time user, please create your candidate login account before you apply for a job. (Click Sign In &gt; Create Account)2. If you already have a Candidate Account, please Sign-In before you apply.<h2>Job Description:</h2>Broadcom is a leading global company in infrastructure technology, data center networking, and security, built on decades of innovation, collaboration, and engineering excellence. The Application Networking and Security (ANS) division develops advanced security solutions—including distributed firewall and micro-segmentation technologies—that protect east-west traffic across enterprise data centers. We have an exciting opportunity for a Member of Technical Staff (Professional 4) to join our Security Intelligence Big Data and Analytics team.Today&#39;s enterprise networks face an expanding attack surface and an ever-changing threat landscape. Our team is on a mission to meet this challenge by delivering powerful, cutting-edge capabilities for VMware vDefend Advanced Threat Prevention (ATP) and the VMware vDefend Firewall.Hosted on the Security Services Platform (SSP), Security Intelligence is a state-of-the-art analytics platform that provides deep network security visibility within virtualized data centers. It streamlines software-defined Layer 3-7 firewall network segmentation by offering graphical visualization of workloads and traffic flows, alongside automated security policy recommendations that enable micro-segmentation at massive scale.Our team is looking for engineers who share our passion for innovation in distributed systems, container networking, and big data. You will be working within a massive, polyglot repo using technologies like Kubernetes, Kafka, Redis, MinIO, Apache Spark, and PostgreSQL to empower Security Analysts to keep their environments safe from malicious threats.What You&#39;ll Actually Work On<ul><li>Network Policy &amp; Micro-segmentation — Building the analytics engines that generate dynamic policy recommendations to eliminate lateral threat movement.</li><li>Datacenter-Wide Graphical Visualization — Delivering comprehensive, near real-time graphical visualization of Applications, Groups, VMs, IPs, and aggregated network traffic flows to provide deep visibility into complex modern applications.</li><li>Metadata Ingestion &amp; &#34;Security as Code&#34; — Building robust data pipelines to ingest Configuration Management Database (CMDB) metadata, automating the definition of hierarchies, bulk tag assignments, group creation, and policy bootstrapping—reducing segmentation planning from months to minutes.</li><li>Continuous Segmentation Monitoring &amp; Drift Detection — Developing tools that continuously monitor network traffic to surface new or unapproved flows, track traffic leakage (for infrastructure workloads and between environments), and alert administrators to unauthorized activity, ensuring continuous compliance.</li><li>Runtime Threat Detection &amp; High-Throughput Streaming — Building detection capabilities that identify anomalous behavior and policy violations using high-throughput data processing systems.</li><li>Distributed &amp; Stateful Workloads — Configuring and managing workloads that require consensus, replication, and fault tolerance—including analytical databases and message buses running on Kubernetes via Operators or StatefulSets.</li></ul>How You&#39;ll Work<ul><li>Own components end-to-end — From breaking down ambiguous problems into clear technical design specs, test driven development through to production support.</li><li>Develop Polyglot Systems — Writing highly performant and scalable code using Go, Java, and Python.</li><li>Debug across layers — Diagnosing complex issues spanning the Kubernetes control plane, networking (TCP/UDP, HTTP, Antrea CNI, Envoy proxies), and cluster-level stateful workloads using Prometheus, Grafana, kubectl debug, and audit logs.</li><li>Build automated tests — Validating security correctness and OpenAPI compliance to prevent regressions in a highly scalable micro-service environment.</li><li>Collaborate across teams — Working closely with platform, UI, and QA engineers, while sharing knowledge and mentoring junior engineers.</li><li>Ship in agile sprints — Participating in all phases of the software development cycle, utilizing Jira, Confluence, and Git-based workflows.</li></ul>What Makes You a Strong Fit<ul><li>Kubernetes Internals — Hands-on experience with Kubernetes architecture and cluster management.</li><li>Strong Programming Skills — Deep expertise in Go, Java (big data, stream processing, Spring/SpringBoot), and Python.</li><li>Distributed Systems &amp; Stateful Workloads — Experience managing consensus, replication, fault tolerance, and running databases (e.g., PostgreSQL-HA, Redis) on Kubernetes.</li><li>High-Volume Data Systems — Experience with analytical databases (e.g., Apache Druid, ClickHouse), large-scale data ingestion (Kafka), and complex querying workloads.</li><li>Modern Build Tooling — Experience working in large repos using advanced build systems like Bazel, alongside Docker/Helm deployments.</li><li>Collaborative Mindset — Ability to work independently on complex problems while collaborating across a global team with a &#34;Team First&#34; mentality.</li><li>Experience with VMware vDefend / DFW is a strong plus.</li></ul>Education &amp; Experience<ul><li>Bachelor&#39;s degree in Engineering/Computer Science and 8&#43; years of related experience, or Master&#39;s degree in Engineering/Computer Science and 6&#43; years of related experience.</li></ul>Additional Job Description:Compensation and BenefitsThe annual base salary range for this position is $120,000 - $192,000 This position is also eligible for a discretionary annual bonus in accordance with relevant plan documents, and equity in accordance with equity plan documents and equity award agreements.Broadcom offers a competitive and comprehensive benefits package: Medical, dental and vision plans, 401(K) participation including company matching, Employee Stock Purchase Program (ESPP), Employee Assistance Program (EAP), company paid holidays, paid sick leave and vacation time. The company follows all applicable laws for Paid Family Leave and other leaves of absence.Broadcom is proud to be an equal opportunity employer.  We will consider qualified applicants without regard to race, color, creed, religion, sex, sexual orientation, national origin, citizenship, disability status, medical condition, pregnancy, protected veteran status or any other characteristic protected by federal, state, or local law.  We will also consider qualified applicants with arrest and conviction records consistent with local law.If you are located outside USA, please be sure to fill out a home address as this will be used for future correspondence.

Software Engineer

8+ years in engineering roles; strong Go/Java/Python; Kubernetes; distributed systems; large-scale data.

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