Explore 4 python full stack developer jobs from 2 hiring companies in Colwich, KS, US. Filter by remote, salary, experience, and company, then open any listing to apply.

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Python Full Stack Developer Jobs

Knowmadics

Wolters Kluwer

Hybrid

Onsite

Job Purpose/Summary 
 
The Geospatial Software Engineer designs, builds, and operates scalable geospatial systems that transform complex spatial-temporal and sensor-derived data into analytics, visualizations, and web-based applications. This role spans the full data path from curated datasets and geospatial processing pipelines through to low-latency APIs and analyst-facing, map-based tools. 
  
Working across backend infrastructure and front-end visualization, the engineer transforms spatial-temporal data and develops robust analytics. They ensure that data pipelines, databases, and web applications are performant, reliable, and designed for real-world operational use. 
  
In close collaboration with data scientists, geophysicists, and cross-functional engineering teams, this role translates advanced research and sensor analytics into scalable systems. As part of a fast-moving, government-funded technology business, the Geospatial Software Engineer operates with high ownership in an applied research environment focused on delivering impactful, mission-driven solutions. 
 
Duties and Responsibilities 
<ul>
<li>Design and build scalable geospatial data pipelines from curated data </li>
</ul>
<ul>
<li>Develop and operationalize spatial-temporal analytics, including movement characterization, clustering, and advanced spatial transformations. </li>
</ul>
<ul>
<li>Translate complex geospatial workflows into reliable, low-latency APIs that power web-based analytical tools. </li>
</ul>
<ul>
<li>Build and maintain interactive, map-based applications for analysts exploring sensor-derived, spatial-temporal data. </li>
</ul>
<ul>
<li>Deploy and operate services in a cloud-native environment using containerized infrastructure. </li>
</ul>
<ul>
<li>Collaborate with data scientists and domain experts to operationalize advanced analytics into robust systems. </li>
</ul>
<ul>
<li>Take ownership of features from backend ingestion through to front-end visualization in an applied research environment. </li>
</ul>
 
Qualifications 
 
Minimum: 
<ul>
<li>3+ years of hands-on geospatial software engineering experience. </li>
</ul>
<ul>
<li>Strong Python geospatial experience, including libraries such as GeoPandas, Shapely, PyProj, and similar tooling. </li>
</ul>
<ul>
<li>Solid understanding of spatial modelling, projections, zonal statistics, and spatial transformations. </li>
</ul>
<ul>
<li>Experience working with spatial-temporal datasets. </li>
</ul>
<ul>
<li>Experience building ETL/data pipelines loadingdata into operational databases such as PostgreSQL with PostGIS/TimescaleDB. </li>
</ul>
<ul>
<li>Experience developing full-stack applications using Python-based backends, FastAPI/Pydantic preferred, and modern JavaScript front-end frameworks with React. </li>
</ul>
<ul>
<li>Experience building geospatial visualizations using libraries such as Cesium, Mapbox/MapLibre, or Lonboard. </li>
</ul>
<ul>
<li>Experience working in AWS or similar cloud environments. </li>
</ul>
<ul>
<li>Experience deploying containerized applications using Docker and familiarity with Kubernetes. </li>
</ul>
<ul>
<li>Eligible to obtain a U.S. Security Clearance – U.S. Citizenship required </li>
</ul>
Preferred: 
<ul>
<li>Direct experience processing geophysical, sensor, or seismographic data. </li>
</ul>
<ul>
<li>Experience developing CI/CD pipelines for data services using Git-based workflows and infrastructure-as-code principles. </li>
</ul>
<ul>
<li>Experience with event-driven or streaming data systems e.g. Kafka, Spark, Flink, or Sedona. </li>
</ul>
<ul>
<li>Experience with lakehouse-style analytical tables e.g. Iceberg or Delta  </li>
</ul>
<ul>
<li>Experience with SQL query engines e.g. Trino, DuckDB, or Athena </li>
</ul>
<ul>
<li>Strong production experience with PostgreSQL with PostGIS and TimescaleDB extensions at scale. </li>
</ul>
<ul>
<li>Experience working with cloud-native geospatial architectures and cloud-optimized formats. </li>
</ul>
<ul>
<li>Experience scaling geospatial workloads in Kubernetes-based environments. </li>
</ul>
<ul>
<li>Experience applying ML/AI techniques, e.g. Bayesian methods and neural networks, to spatial-temporal datasets. </li>
</ul>
<ul>
<li>Background in defense, cybersecurity, space, or other mission-driven sensor analytics environments. </li>
</ul>
Working conditions 
 
<ul>
<li>Employees may be called upon to participate in in-person meetings, trainings, or company functions at Knowmadics offices or other designated locations. Travel in support of business operations may also be required, and employees are expected to comply with these obligations as part of their position. </li>
</ul>
 
 
Physical requirements 
 
May include sitting or standing for extended periods, working with computers and technical equipment, and occasionally lifting or moving materials or tools. 
 
Direct reports 
 
None

Software Engineer, Geospatial

Software Engineer

3+ years geospatial software engineering; strong Python geospatial stack; ETL pipelines; full-stack Python + React; AWS; Docker/Kubernetes; eligible for U.S. security clearance.

Job Purpose/Summary 
 
The MLOps Engineer designs, builds, and operates scalable machine learning systems that transform spatial-temporal and sensor-derived data into reliable ML workflows. This role spans the full ML lifecycle ingest, normalization, and feature engineering pipelines through distributed training and evaluation to low-latency inference and operational integration. 
  
Working across data infrastructure and deployment environments, the engineer operationalizes experimental models into reproducible, observable, and scalable systems. They ensure ML pipelines, containerized workloads, and CI/CD processes are robust, automated, and designed for real-world operational demands. 
  
In close collaboration with data scientists, geophysicists, and cross-functional engineering teams, this role translates research-grade algorithms into resilient services. As part of a fast-moving, government-funded technology business, the MLOps Engineer operates with high ownership in a low-ceremony, applied research environment, bringing structure, repeatability, and best practices to mission-driven sensor analytics systems. 
 
Duties and Responsibilities 
 
<ul>
<li>Design, build, and operate scalable ML and data pipelines for spatial-temporal and sensor-driven datasets. </li>
</ul>
<ul>
<li>Operationalize data science algorithms into reliable, distributed ML workflows covering feature extraction, training, evaluation, inference, and model lifecycle management. </li>
</ul>
<ul>
<li>Implement and maintain containerized ML workloads in cloud-native environments. </li>
</ul>
<ul>
<li>Integrate model outputs into downstream serving systems and analytical platforms to support web-based applications and operational decision-making. </li>
</ul>
<ul>
<li>Develop and maintain CI/CD pipelines for ML and data services. </li>
</ul>
<ul>
<li>Collaborate closely with data scientists to operationalize experimental models into reproducible, observable, and scalable production systems. </li>
</ul>
<ul>
<li>Take ownership of MLOps practices within an applied research team, bringing structure, repeatability, and best practices to evolving environments. </li>
</ul>
 
Qualifications 
 
Minimum: 
<ul>
<li>3+ years of experience in MLOps, ML Engineering, Data Engineering, or closely related roles building and running ML/data pipelines. </li>
</ul>
<ul>
<li>Strong Python data and ML stack experience, including tools such as Polars/Pandas, PyArrow, PySpark, NumPy/SciPy. </li>
</ul>
<ul>
<li>Experience integrating models built with frameworks such as PyTorch, TensorFlow, or Keras into scalable pipelines. </li>
</ul>
<ul>
<li>Demonstrated experience working with temporal data, ideally including sensor-derived signals. </li>
</ul>
<ul>
<li>Practical CI/CD experience for ML/data services using Git-based workflows. </li>
</ul>
<ul>
<li>Experience working in AWS or similar cloud environments.  </li>
</ul>
<ul>
<li>Experience running containerized ML or data workloads in Kubernetes. </li>
</ul>
<ul>
<li>Experience collaborating closely with data scientists to integrate algorithms. </li>
</ul>
<ul>
<li>Eligible to obtain a U.S. Security Clearance – U.S. Citizenship required. </li>
</ul>
Preferred: 
<ul>
<li>Direct hands-on experience with sensor datasets such as seismographic data, cellular sensor modalities, RF survey data, or GPS devices. </li>
</ul>
<ul>
<li>Experience deploying and scaling ML workloads in Kubernetes using KEDA or alternative event-driven autoscaling approaches. </li>
</ul>
<ul>
<li>Experience building event-driven or streaming pipelines e.g. Kafka, Spark, Flink, or Sedona feeding lakehouse-style open table formats e.g. Iceberg or Delta. </li>
</ul>
<ul>
<li>Experience with SQL query engines e.g. Trino, DuckDB, or Athena </li>
</ul>
<ul>
<li>Experience selecting and operating orchestration frameworks such as Airflow, Dask, Ray, or Spark for scalable ML workloads. </li>
</ul>
<ul>
<li>Strong PostgreSQL experience, ideally with TimescaleDB and/or PostGIS, integrating ML outputs into operational databases. </li>
</ul>
<ul>
<li>DevOps experience with Helm and GitOps tooling. </li>
</ul>
<ul>
<li>Background in defense, cybersecurity, space, or other mission-driven sensor analytics environments. </li>
</ul>
 
Working conditions 
 
<ul>
<li>Employees may be called upon to participate in in-person meetings, trainings, or company functions at Knowmadics offices or other designated locations. Travel in support of business operations may also be required, and employees are expected to comply with these obligations as part of their position. </li>
</ul>
 
Physical requirements 
 
May include sitting or standing for extended periods, working with computers and technical equipment, and occasionally lifting or moving materials or tools. 
 
Direct reports 
 
None

MLOps Engineer

3+ years in MLOps/ML/data engineering; Python stack; PyTorch/TensorFlow/Keras; AWS; Kubernetes; CI/CD; sensor data; eligible for U.S. security clearance.

<div>We&#39;re looking for a Senior Product Software Engineer - AI to join InnovateHub, our startup-within-the-enterprise that co-designs AI solutions with customers across Wolters Kluwer&#39;s Tax and Accounting product portfolio. You&#39;ll develop cutting-edge AI features that transform how accounting professionals work, focusing on real customer problems rather than technology-first solutions. </div><div> </div><div>InnovateHub operates with close collaboration between engineers, product managers, UX designers, and researchers. Engineers deeply understand business problems, product managers rapidly prototype ideas, and designers and researchers translate user needs into elegant, evidence-based solutions. We work in fast feedback cycles, obsess over customer value, and blur traditional role boundaries to focus on solving the right problems. We practice Agile and XP methodologies with weekly sprints, BDD/TDD practices, and pair programming with daily rotation to support high team cohesion and knowledge sharing. </div><div> </div><div>This role is ideal for someone who adapts quickly to new technologies, communicates effectively across teams, thrives in collaborative environments, and is passionate about human-centric AI solutions that deliver real value to professionals. </div><div> </div><div>Key Responsibilities: </div><div>Customer-Centric Product Development: Co-design AI solutions with customers, focusing on real problems rather than technology-first approaches. Build human-centric AI features that deliver measurable value in fast feedback cycles. </div><div> </div><div>Cross-Functional Collaboration: Collaborate across engineering disciplines and product roles (product managers, designers, other engineers) within project domains, building AI solutions that integrate seamlessly with broader team efforts and customer value streams. </div><div> </div><div>Technical Contribution: Implement AI features using Python and modern frameworks, contributing to intelligent document processing, automated workflows, and AI-powered analytics within defined technical direction, with a focus on code quality, security, and product experience. </div><div> </div><div>Technical Advisory: Exercise independent judgment on technical design decisions within AI systems; serve as a collaborative resource for the pod on complex problem-solving, architectural trade-offs, and best practices. </div><div> </div><div>Close Collaboration: Work in InnovateHub&#39;s collaborative model where engineers understand business problems as deeply as technical solutions, partnering closely with product managers who prototype their own ideas. </div><div> </div><div>Communication Skills: Ability to explain technical concepts to non-technical stakeholders and drive adoption of new technologies across teams. </div><div> </div><div><div>Requirements: </div><div>Technical Foundation:  </div><div><ul><li>3&#43; years building software applications (experience with Python, JavaScript/TypeScript preferred) </li></ul></div><div><ul><li>Full-stack development capabilities </li></ul></div><div><ul><li>Experience with Agile/XP practices including TDD/BDD and pair programming </li></ul></div><div><ul><li>Proficiency with AI coding tools (GitHub Copilot, Cursor, or similar)  </li></ul></div><div><ul><li>Regular use of GenAI utilities (ChatGPT, Claude, etc.) for development workflow </li></ul></div><div><ul><li>Exposure to or strong interest in AI/ML workflows, LLM APIs (e.g., OpenAI, Azure AI), or AI frameworks (e.g., LangChain, Hugging Face) </li></ul></div><div> </div><div>Project Delivery:  </div><div><ul><li>1&#43; years delivering complex technical projects from inception to delivery </li></ul></div><div><ul><li>Experience working in startup-like environments or innovation teams </li></ul></div><div><ul><li>Comfort working in collaborative, fast-paced Agile environments with weekly sprints and blurred (but aligned) role boundaries </li></ul></div><div> </div><div>Preferred Qualifications: </div><div><ul><li>Experience with Azure AI services, advanced AI frameworks, or multi-modal AI systems </li></ul></div><div><ul><li>Background in dynamic environments like startups, innovation teams, or product-focused companies that prioritize customer co-design and rapid value delivery </li></ul></div><div><ul><li>Experience with document processing, financial data analysis, or B2B professional software </li></ul></div><div><ul><li>Experience with MLOps, AI governance, or cross-portfolio AI implementations, particularly in regulated/compliance-driven environments </li></ul></div><div><ul><li>Microsoft Azure AI App and Agent Developer Associate certification is a valued growth target. Our team prioritizes AI application development expertise and we welcome candidates motivated to achieve this credential </li></ul></div></div><div> </div><div>We encourage applications from candidates with diverse backgrounds who have strong technical skills, project leadership experience, and can adapt quickly to new challenges in a customer-focused, innovation-driven environment. </div><div> </div><div>Our Culture:  At Wolters Kluwer, our core values—Focus on Customer Success, Make it Better, Aim High and Deliver, and Win as a Team—guide everything we do. We are committed to driving success for our customers by delivering innovative solutions that exceed expectations. We continually strive to improve our processes and products, aiming for excellence in all our efforts. Collaboration and teamwork are central to our culture, enabling us to achieve great results together. </div><h2>Our Interview Practices</h2>To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process. Compensation:$92,700.00 - $161,850.00 USD This role is eligible for Bonus.Compensation range listed is based on primary location of the position.  Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process. <h2>Additional Information:</h2>Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, &amp; Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.

Sr. Product Software Engineer - AI

Product Software Engineer

3+ years software development; full-stack; Agile/XP with TDD/BDD and pair programming; experience with AI tools and ML workflows.

Wolters Kluwer Tax&amp; Accounting team is looking for a Lead Software Engineer to build the next generation of AI-powered capabilities for our cloud audit solutions. You will build AI -powered audit solutions that help professionals analyze complex documents, interpret rules, detect exceptions and generate explainable findings.Our team operates with close collaboration between engineers, product managers, UX designers, and researchers. Engineers deeply understand business problems, product managers rapidly prototype ideas, and designers and researchers translate user needs into elegant, evidence-based solutions. We work in fast feedback cycles, obsess over customer value, and blur traditional role boundaries to focus on solving the right problems. We practice Agile and XP methodologies with weekly sprints, BDD/TDD practices, and pair programming with daily rotation to support high team cohesion and knowledge sharing.This role is ideal for someone who adapts quickly to new technologies, communicates effectively across teams, thrives in collaborative environments, and is passionate about human-centric AI solutions that deliver real value to professionals.Key Responsibilities:Build AI Agent Systems: Design and implement task-focused AI agents that assist thousands of professional’s audit work. Building Document understanding and structured-data extraction systems. Leading production-grade AI services and shipping working capabilities quickly and iterating with Product &amp; customer teams.Cross-Portfolio Innovation: Work across TAA&#39;s product portfolio, enabling other teams while building AI solutions that can be applied to multiple products and customer segments.Technical Leadership: Design and implement AI features using Python and modern frameworks. Build intelligent document processing, automated workflows, and AI-powered analytics with a focus on security, product experience, and scalability.Close Collaboration: Work in Audit’s collaborative model where engineers understand business problems as deeply as technical solutions, partnering closely with product managers who prototype their own ideas.Requirements:Technical Foundation:<ul><li>Bachelors Degree in Computer Science or Equivalent</li><li>5&#43; years building software applications (experience with Python, Java or C&#43;&#43;)</li><li>1&#43; years hands-on experience with LLMs or AI systems (NLP preferred)</li><li>Full-stack development capabilities</li><li>Experience with Agile/XP practices including TDD/BDD and pair programming</li><li>Proficiency with AI coding tools (GitHub Copilot, Cursor, or similar)</li><li>Regular use of GenAI utilities (ChatGPT, Claude, etc.) for development workflow</li></ul>Technical Project Leadership:<ul><li>3&#43; years leading complex technical projects from inception to delivery</li><li>Experience working in startup-like environments or innovation teams</li><li>Comfort working in collaborative, fast-paced Agile environments with weekly sprints and blurred (but aligned) role boundaries</li></ul>AI/ML Experience:<ul><li>Working knowledge of AI/ML frameworks (LangChain, Langgraph, Hugging Face, OpenAI APIs)</li><li>Experience with vector databases and embeddings</li><li>Understanding of prompt engineering and AI optimization</li></ul>Communication Skills: Ability to explain technical concepts to non-technical stakeholders and drive adoption of new technologies across teams.Preferred Qualifications:Microsoft Azure AI-102 certification is highly desired or able to get certified in first 30 days - our team is 100% certified and we value this demonstration of Azure AI expertise<ul><li>Experience with Azure AI services, advanced AI frameworks, or multi-modal AI systems</li><li>Background in dynamic environments like startups, innovation teams, or product-focused companies that prioritize customer co-design and rapid value delivery</li><li>Experience with document processing, financial data analysis, or B2B professional software</li><li>Experience with MLOps, AI governance, or cross-portfolio AI implementations, particularly in regulated/compliance-driven environments</li></ul>We encourage applications from candidates with diverse backgrounds who have strong technical skills, project leadership experience, and can adapt quickly to new challenges in a customer-focused, innovation-driven environment.Our Culture: At Wolters Kluwer, our core values—Focus on Customer Success, Make it Better, Aim High and Deliver, and Win as a Team—guide everything we do. We are committed to driving success for our customers by delivering innovative solutions that exceed expectations. We continually strive to improve our processes and products, aiming for excellence in all our efforts. Collaboration and teamwork are central to our culture, enabling us to achieve great results together.<h2>Our Interview Practices</h2>To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process. Compensation:$116,400.00 - $204,100.00 USD This role is eligible for Bonus.Compensation range listed is based on primary location of the position.  Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process. <h2>Additional Information:</h2>Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, &amp; Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.

Lead Product Software Engineer - AI

Lead Product Software Engineer

Bachelor's in CS, 5+ years software development, 1+ year AI/LLM, full-stack, Agile/XP, GenAI tools.

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