Full Stack Python Developer

Column Technical Services•Chicago, IL

1d•Onsite

About The Position

Column Technical Services is seeking a seasoned Full Stack Python Developer with strong experience in FastAP I to join a high-performing agile team. This individual will design, build, and support scalable backend systems and APIs, while also contributing to broader full-stack initiatives that address complex business needs. Success in this role requires strong proficiency in Python, modern frameworks, database systems, and established engineering practices. If this opportunity aligns with your experience and interests, we encourage you to apply and begin the conversation with us. This position does not provide sponsorship. Candidates must currently reside in the Chicagoland area. Role Overview This position is suited for a systems-minded professional who thrives in fast-moving environments and naturally leverages AI as a primary tool rather than a fallback. You will operate at the intersection of product and engineering, continuously experimenting and helping to deliver AI-driven solutions that perform effectively in real-world scenarios. Your day-to-day work may range from implementing large language model integrations to reimagining how workflows function from the ground up. Frequent context shifts are part of the role—and are expected to energize, not disrupt, your productivity.

Requirements

2+ years of experience with cloud platforms such as Azure (or equivalent)
2+ years working with open-source frameworks, including FastAPI and FastLLM
2+ years of hands-on experience with Agile delivery practices
Highly adaptable with a genuine interest in staying current in a rapidly evolving AI landscape
Action-oriented mindset, with a preference for testing and iterating rather than over-planning
Strong familiarity with AI tools and a forward-thinking approach to their application
Ability to quickly learn new technologies and frameworks independently
Demonstrated experience building and deploying high-scale, distributed transactional systems
Strong proficiency in Python and FastAPI (or similar asynchronous frameworks)
Practical experience working with relational databases, such as Microsoft SQL Server
Exposure to large language model integrations (OpenAI, Anthropic, etc.)
Understanding of RESTful API design and backend development fundamentals
Experience with Git and collaborative version control workflows
Familiarity with testing frameworks like pytest or unittest
Experience working within Agile methodologies (Scrum or Kanban) and understanding of SDLC processes
Solid grasp of database design, querying, and data access patterns
Experience developing applications using modular, component-based frameworks
Strong communication skills, with the ability to collaborate across technical and non-technical audiences
Commitment to modern development practices for enterprise application delivery

Responsibilities

Design and continuously refine AI-driven workflow systems using modern agent-based frameworks
Develop agent capabilities, supporting tools, and safeguards to ensure system reliability and predictability
Integrate and optimize large language model APIs (e.g., OpenAI, Anthropic) for performance and efficiency
Create evaluation frameworks to assess output quality and detect regressions early
Quickly prototype and validate new concepts through hands-on experimentation
Remain actively informed on advancements in AI and share relevant findings with the team
Partner with product managers and stakeholders to clarify requirements and translate them into technical solutions
Execute proof-of-concept initiatives to validate ideas and reduce implementation risk
Write high-quality, maintainable, and well-tested code aligned with defined acceptance criteria and compliance needs
Architect scalable components across data, application, and business layers
Diagnose and resolve technical issues throughout development and integration
Develop and maintain automated testing suites, including unit, integration, regression, and performance tests
Ensure solutions adhere to enterprise architecture standards across the development lifecycle
Support production releases, including deployments, patches, and enhancements
Troubleshoot production issues and improve system performance and reliability