Explore 4 python cloud platform developer jobs from 1 hiring companies in Tool, TX, US. Filter by remote, salary, experience, and company, then open any listing to apply.

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Python Cloud Platform Developer Jobs

Goldman Sachs

Onsite

The Runtime Platforms team delivers&nbsp;a highly available&nbsp;and scalable ecosystem for Goldman Sachs engineers worldwide, enabling them to run workloads across various compute platforms. As part of the firm's strategic move to increase the usage of containerization to package, deliver and run software, the runtime team plays a critical role in ensuring that we offer container platforms that are secure, reliable and operationally inexpensive so that business teams can focus on delivering value to shareholders. The platforms offered by the runtime team support some of the firm's most critical businesses and services both on-premises and in public cloud.
At Goldman Sachs, our culture is one of teamwork,&nbsp;innovation&nbsp;and meritocracy. We often say our people are our greatest asset and we take pride in supporting each colleague both professionally and personally. You will be joining a talented globally distributed team passionate about delivering the best possible experience to our users.&nbsp; This is an experienced-hire role for a self-directed engineer who will act as the regional subject matter expert (SME) for the Procmon platform.
Procmon Platform delivers a highly scalable and reliable ecosystem for scheduling business critical jobs across Goldman Sachs.
Our platform is responsible for scheduling tens of millions of daily jobs for Global Banking &amp; Markets, Asset &amp; Wealth Management, Risk and other business and engineering functions.
The ecosystem includes a number of high availability, very large scale systems including
<ul>
 <li>Job scheduling</li>
 <li>Event streaming</li>
 <li>Log shipping</li>
 <li>Data warehouses</li>
 <li>Security infrastructure 
 &nbsp;</li>
</ul>
RESPONSIBILITIES
<ul>
 <li>Proactively identify operational risks, capacity concerns and reliability gaps; propose and implement remediation without requiring close supervision.</li>
 <li>Continuously refine runbooks, tooling and automation to reduce manual toil and improve platform reliability.</li>
 <li>Build observability for new deployments to ensure robustness. Work closely with development team to ensure observability is built in from the start.</li>
 <li>Lead real-time outage investigations, write and present postmortems to senior management.</li>
 <li>Define SLIs and SLOs and partner with development teams to ensure system are well designed and live up to our SLAs.</li>
 <li>Work closely with users to facilitate planned migration from the previous to the newest Procmon platform.</li>
 <li>Communicate well and work efficiently with remote colleagues in other regions.</li>
 <li>Provide regional coverage for the Procmon platform, including participation in an on-call rotation and acting as the escalation point for user queries and L3 escalations.</li>
</ul>
&nbsp;
REQUIREMENTS
<ul>
 <li>Extensive experience (8+ years) in DevOps or Production Engineering, with expertise in architecting, deploying, and scaling distributed computing systems,</li>
 <li>Excellent problem-solving and automation skills, leveraging real-time monitoring and alerting tools like Prometheus for proactive incident detection and automated response, and utilizing data analysis and Grafana for historical data visualization, deep-dive root cause analysis, and automated operational reporting.</li>
 <li>Deep knowledge of Linux operating systems and system administration</li>
 <li>Good networking fundamentals (familiarity with TCP/IP, IP routing, firewalls, secure tunneling protocols).</li>
 <li>Experience working with distributed computing systems and Cloud computing within enterprise environments.</li>
 <li>Proficiency in at least one programming language; the team uses a mix of Go, Shell, Python and Erlang</li>
 <li>Able to operate effectively in a mission critical, highly regulated financial services environment.</li>
 <li>Strong communication skills, able to explain complex technical issues clearly to both technical and non-technical users.</li>
 <li>Previous experience with supporting and mentoring junior team members and interns is a plus.</li>
</ul>

Engineering - DXR Engineering - Senior Scheduling Platform Production Engineer - Dallas - Vice President

Senior Scheduling Platform Production Engineer

8+ years DevOps/Production Engineering; automation, monitoring (Prometheus, Grafana); Linux, networking; cloud experience; programming in Go, Shell, Python, or Erlang.

Job Title:&nbsp;AI Solutions Engineer – Vice President
Division:&nbsp;Asset &amp; Wealth Management – WM Data Engineering
What We Do
At Goldman Sachs, our Engineers don't just make things — we make things possible. The Wealth Management (WM) Data Engineering team within Asset &amp; Wealth Management builds and operates the data ecosystem that powers Wealth Management at scale — migrating legacy on-premises workloads to cloud-native platforms, delivering Lakehouse architecture on AWS, and embedding AI into how we build, operate, and evolve that infrastructure.
Our AI Solutions Engineering function bridges applied AI with data engineering — designing intelligent agent-based systems, LLM-powered tooling, and AI-augmented workflows that operate directly on the firm's data assets, pipelines, and governance surfaces.
Who We Look For
We are seeking an experienced AI Solutions Engineer to lead the design, development, and operationalization of production AI systems purpose-built for a modern data engineering organization. You are equally comfortable prototyping with large language models and reasoning about pipeline architecture, schema evolution, and query performance. You bring technical leadership that elevates the people around you.
Responsibilities
<ul>
 <li>Architect and deliver AI-powered data engineering solutions — LLM agents, RAG pipelines, and multi-agent workflows for pipeline generation, schema mapping, data quality, and migration — using tool-calling, stateful memory, and multi-agent coordination, integrated with the WM Lakehouse platform (S3, Databricks, Snowflake, Glue, Athena, MWAA)</li>
 <li>Define and maintain AI evaluation standards: offline benchmarks, prompt versioning, regression testing, and production observability — so the team always knows when a system is degrading</li>
 <li>Own the AI delivery lifecycle — CI/CD for model artifacts and prompt configurations, automated regression testing, and release management for LLM-powered services</li>
 <li>Enforce responsible AI practices: output guardrails, prompt injection defenses, and PII handling in LLM pipelines that operate on sensitive financial data</li>
 <li>Partner with data architects and platform engineers to ensure AI systems comply with data governance and regulatory standards (GDPR, CCPA, SOC2) and leverage Lakehouse infrastructure (Iceberg, Lake Formation)</li>
 <li>Establish and evangelize AI integration patterns (Model Context Protocol, AWS Bedrock) that enable data platform teams to expose their tools and data sources to LLM-based agents</li>
 <li>Mentor and develop associate and analyst engineers; provide technical direction and code review</li>
</ul>
Basic Qualifications
<ul>
 <li>7+ years of software engineering experience, with 3+ years’ building production AI/ML systems and demonstrated experience in LLM-based or agentic architectures</li>
 <li>Proficiency in Java, Python, and SQL; strong hands-on experience with LLM APIs (OpenAI, Anthropic, or equivalent) and agentic frameworks (LangChain, LangGraph, or similar)</li>
 <li>Demonstrated experience designing agentic architectures: tool use, multi-agent orchestration, memory, and state management</li>
 <li>Working knowledge of cloud data platforms — S3, Glue, Snowflake, Athena, MWAA/Airflow, Lambda, Lakehouse patterns, and ETL/ELT workflows</li>
 <li>Experience building AI evaluation pipelines (LangSmith, RAGAS, PromptFoo, or equivalent)</li>
 <li>Excellent communication skills; proven ability to lead cross-functional technical initiatives</li>
</ul>
Preferred Qualifications
<ul>
 <li>Experience with standardized tool-integration patterns for LLM agents (e.g., Model Context Protocol) or equivalent approaches for exposing APIs and data sources to agentic systems</li>
 <li>Experience with data governance tooling — metadata management, data lineage, data quality frameworks, or AWS Lake Formation</li>
 <li>Familiarity with modern data formats and engines (Apache Iceberg, Spark, Databricks, Snowflake)</li>
 <li>Experience with event-driven architecture, streaming pipelines, or real-time inference serving</li>
 <li>Experience with infrastructure as code (AWS CDK, Terraform, or CloudFormation)</li>
 <li>Background in financial services or regulated data environments</li>
</ul>
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 ABOUT GOLDMAN SACHS
</div>
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</div>
<div>
 At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.&nbsp;
</div>
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 &nbsp;
</div>
<div>
 We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.&nbsp;
</div>
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</div>
<div>
 We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html
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 © The Goldman Sachs Group, Inc., 2023. All rights reserved.
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<div>
 <div>
 Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
 </div>
</div>

Asset & Wealth Management-AI Solutions Engineer-Vice President-Dallas

AI Solutions Engineer

7+ years software engineering; 3+ years building production AI/ML systems; proficient in Java, Python, SQL; experienced with LLM APIs and agent frameworks; strong cloud data platform experience; AI evaluation pipelines; excellent communication.

Site Reliability Engineering (SRE) is an engineering discipline that combines software development and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. At Goldman Sachs, SRE is responsible for the availability and reliability of our firm's most critical platform services and ensures they meet the requirements of our internal and external users. We also develop and operate the observability platforms that all other engineering teams use to make their services reliable. We look for engineers who are motivated to collaborate with other engineering teams and our businesses to build and run sustainable production systems, which can evolve and adapt to changes in our fast-paced, global business and regulatory environment.
How will you fulfil your potential?
<ul>
 <li>Balance feature development velocity and reliability with well-defined SLOs.</li>
 <li>Run the Production environment by monitoring availability and taking a holistic view of system health.</li>
 <li>Drive incident management process and support a blameless post-mortems culture.</li>
 <li>Partner with development teams to improve services via rigorous testing and release procedures.</li>
 <li>Participate in system design consulting, platform management, and capacity planning.</li>
 <li>Create sustainable systems and services through automation and uplifts.</li>
 <li>Champion reliability and resilience engineering practices and knowledge across the firm.</li>
</ul>
Basic Qualifications
<ul>
 <li>Minimum of 2+ years of hands-on experience in Site Reliability Engineering, with a proven track record in building, and maintaining highly available, scalable, and fault-tolerant systems at an enterprise level.</li>
 <li>BS degree in Computer Science or related technical field involving coding and / or systems engineering.</li>
 <li>Proficiency in one or more of the following: Go, Python, C, C++, Java, Perl, Ruby or shell scripting.</li>
 <li>Experience with product engineering practices, algorithms, data structures, software design and/or Experience with UNIX operating systems internals and / or networking.</li>
</ul>
Preferred Qualifications
<ul>
 <li>Experience in developing AI tools and working with Cloud Platforms</li>
 <li>Experience with distributed systems design, maintenance, and troubleshooting.</li>
 <li>Hands-on experience with debugging and optimizing code, as well as automation.</li>
 <li>Strong interpersonal skills, drive, and ownership. </li>
 <li>Coding beyond simple scripts.</li>
 <li>Solving novel problems from first principles.</li>
 <li>Experience working in highly regulated, financial services firms.</li>
 <li>Excellent people leadership skills either as an engineering manager or individual contributor</li>
</ul>

Engineering - SRE Platforms - SRE Engineer - Associate - Dallas

SRE Engineer

2+ years in Site Reliability Engineering; BS in CS or related field; proficient in Go, Python, Java, C/C++, Perl, Ruby or shell; UNIX/networking experience; cloud and distributed systems exposure.

Site&nbsp;Reliability&nbsp;Engineer - Vice President
Site Reliability Engineering (SRE) is an engineering discipline that combines software and systems engineering to build and run scalable, massively distributed, fault-tolerant systems. At Goldman Sachs, SRE is responsible for improving the availability and reliability of the firm’s most critical platform services and ensures they meet the requirements of our internal and external users. It is also responsible for firmwide policies and standards focused on firm’s digital resilience. We are looking for engineers who are motivated to collaborate with our businesses to build and run sustainable production systems, which can evolve and adapt to changes in our fast-paced, global business environment.
&nbsp;
The SRE team develops and maintains platforms and tools which help other Engineering teams in Goldman Sachs to build and operate reliable and resilient systems. These systems span on-premises datacenters and multiple public cloud environments.&nbsp; &nbsp;The platforms we offer include central logging, monitoring, agents and alerting and we provide tools to drive adoption and improvements to capacity planning, operational readiness assessments, production incident postmortems, SLIs / SLOs, and deployment automation including canary releases.
&nbsp;
The products and services we provide to our internal customers are used by thousands of engineers every day. We believe that reliability is the most important feature of any system, and we are devoted to giving our engineers the platforms and tools they need to build and operate reliable products.&nbsp; Role Overview
As a Site Reliability Engineer (SRE) at Goldman Sachs, you will be a pivotal leader in ensuring the availability, reliability, and scalability of the firm's most critical platform applications and services. You will combine deep software and systems engineering expertise to architect, build, and run large-scale, massively distributed, fault-tolerant systems. This role involves providing technical leadership, mentoring senior engineers, and collaborating closely with internal teams and executive stakeholders to build and operate sustainable production systems that can adapt to our dynamic global business environment. You will drive a culture of continuous improvement, championing the adoption of advanced SRE principles and best practices across the organization.
&nbsp;Responsibilities
<ul>
 <li>Strategic Reliability &amp; Performance: Drive the strategic direction for availability, scalability, and performance of mission-critical applications and platform services, ensuring alignment with firm-wide objectives.</li>
 <li>Architectural Leadership: Lead the design, build, and implementation of highly available, resilient, and scalable infrastructure and application architectures.</li>
 <li>Advanced Automation &amp; Tooling: Architect and develop sophisticated platforms, tools, and automation solutions to eliminate toil, optimize operational workflows, and enhance deployment processes across the enterprise.</li>
 <li>Complex Incident Management &amp; Post-Mortem Analysis: Lead critical incident response, conduct in-depth root cause analysis for systemic issues, and implement long-term preventative measures to significantly enhance system stability and resilience.</li>
 <li>System Design &amp; Capacity Planning: Partner with development teams to embed reliability into application design from inception, provide expert system design consulting, and lead comprehensive capacity planning initiatives for future growth.</li>
 <li>Observability &amp; Insights: Define and implement advanced monitoring, high volume logging with multi-user query capabilities, and tracing strategies to provide deep, actionable insights into application performance, infrastructure health, and user experience.</li>
 <li>Technical Vision &amp; Mentorship: Provide technical vision, lead complex technical projects, conduct rigorous code reviews, enforce SDLC best practices, and actively mentor and develop senior and staff-level engineers.</li>
 <li>Technology Evaluation &amp; Adoption: Stay at the forefront of industry trends and advancements, evaluating and integrating cutting-edge tools and frameworks to significantly improve operational efficiency and reliability.</li>
 <li>On-Call Leadership: Participate in and lead on-call rotations, providing expert guidance and hands-on support for critical system incidents.</li>
</ul>Qualifications
<ul>
 <li>Experience: Minimum of 6+ years of hands-on experience in Site Reliability Engineering, with a proven track record in architecting, designing, building, and maintaining highly available, scalable, and fault-tolerant systems at an enterprise level.</li>
 <li>Technical Proficiency:
 <ul>
 <li>Exceptional programming skills in one or more major languages such as Java, Python, Go with a focus on building robust, scalable software.</li>
 <li>Extensive hands-on experience with cloud platforms (e.g., AWS, GCP) and deep expertise in containerization and orchestration technologies (e.g., Docker, Kubernetes).</li>
 <li>Mastery of Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation) and configuration management tools (e.g., Puppet, Chef, Ansible).</li>
 <li>Advanced proficiency in Prompt Engineering and Retrieval-Augmented Generation (RAG) architectures to automate complex SRE workflows, such as the generation of Infrastructure as Code (IaC), dynamic runbooks, and incident response summaries.</li>
 <li>Profound understanding of Linux internals, networking, distributed systems, and advanced system performance tuning.</li>
 <li>Expertise in designing and implementing comprehensive monitoring, alerting, logging and tracing solutions (e.g., Prometheus, Grafana, ELK stack, Datadog, PagerDuty).</li>
 <li>Deep experience with CI/CD tools and practices (e.g., Jenkins, GitLab, Maven).</li>
 <li>Strong foundation in databases and distributed systems.</li>
 <li>Exceptional problem-solving abilities and analytical skills, with a track record of resolving complex technical challenges.</li>
 </ul></li>
 <li>Preferred Experience:
 <ul>
 <li>Experience with Distributed Databases like Elastic Search</li>
 <li>Experience with working on GCP Big Query</li>
 <li>Experience with messaging Systems Like Kafka</li>
 </ul></li>
 <li>Education: Advanced degree (Bachelor’s or Mas&nbsp;ter's or PhD) in Computer Science or a related technical field involving coding and/or systems engineering, or equivalent practical experience.</li>
 <li>Soft Skills: Superior communication, collaboration, and interpersonal skills, with the ability to influence technical direction, lead cross-functional initiatives, and effectively engage with global teams and executive leadership. Proven ability to work independently, manage multiple complex stakeholders, and drive significant organizational change.</li>
</ul>
&nbsp;

Engineering - SRE Platforms - Site Reliability Engineer - Vice President - Dallas

Site Reliability Engineer

6+ years SRE experience; strong cloud, automation, monitoring, and incident management; leadership and mentoring abilities.

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