Full Stack Python Engineer

Job Description: Role: Full Stack Python Engineer Location: Hybrid - 4 days/week onsite in SE MI Duration: Long-Term Contract Description: Our organization develops data and AI-enabled products that help better our products while reducing cost and complexity. We are seeking a Senior Python Full Stack Software Engineer to design, build, launch, and support products across portfolio. This is a hands-on engineering role within a small, product-focused team. The engineer will own features end to end, from understanding user needs and designing solutions through development, testing, deployment, and production support. The ideal candidate has strong full-stack development experience across React, Python, relational databases, APIs, and Google Cloud Platform (GCP), along with hands-on experience using AI development tools and an interest in building production-ready LLM and AI-enabled features. Key Responsibilities Full Stack Product Development - Design, build, test, deploy, and support software features across front-end, backend, API, and data layers. - Develop modern web applications using technologies such as React. - Build backend services and APIs using Python and related technologies. - Design and maintain relational data models using technologies such as PostgreSQL. - Develop scalable, reliable, and maintainable applications within Google Cloud Platform (GCP). - Take ownership of features throughout the complete software development lifecycle. - Transform prototypes and proofs of concept into secure, reliable, production-ready software. AI & LLM Integration - Use AI-assisted development tools as part of day-to-day software engineering. - Build and integrate AI and LLM-powered capabilities into production applications. - Develop AI features with appropriate guardrails, evaluation, observability, and human oversight. - Evaluate emerging AI technologies and determine how they can solve practical business and engineering problems. - Where applicable, develop solutions involving agent frameworks, MCP, retrieval-augmented generation (RAG), and LLM evaluation. Architecture & Engineering Practices - Contribute to application architecture, data models, API design, integrations, and technical design decisions. - Evaluate technical trade-offs and recommend solutions that balance speed, maintainability, security, and scalability. - Write automated tests and participate in peer code reviews. - Apply modern CI/CD, security, and observability practices. - Identify technical debt, quality concerns, and engineering risks early and recommend practical solutions. - Integrate applications with existing engineering tools, enterprise data sources, and legacy systems. Product & Business Collaboration - Partner closely with Product Managers, Technical Program Managers, engineers, data scientists, designers, and business stakeholders. - Spend time with engineers and business users to understand their workflows and identify opportunities to improve products. - Translate user problems and business requirements into effective technical solutions. - Communicate technical decisions, trade-offs, risks, and progress clearly to both technical and nontechnical stakeholders. - Use customer feedback and measurable outcomes to continuously improve products. Team Collaboration Share technical knowledge and engineering best practices across the team. Participate in pairing and collaborative development activities.