Full-Stack AI Engineer

Build solutions that matter.

Our teams create full-stack products across established and emerging technologies, choosing the right tools to solve real client challenges. You could be part of:

• Creating the digital experiences people use every day by designing and building modern web and mobile applications with technologies like React, Angular, and Vue.

• Powering business-critical systems at scale through APIs and backend services that enable innovation, performance, and reliability using technologies such as Python, Node.js, and TypeScript.

• Bringing the next generation of AI-powered solutions to life by leveraging cloud platforms and Generative AI services from AWS and Google Cloud to solve complex business problems.

• Driving efficiency and accelerating delivery through automated CI/CD pipelines, modern infrastructure practices, and operational improvements that help teams move faster and smarter.

• Shaping the future of software development by collaborating in agile teams that embrace Generative AI tools and modern engineering practices to deliver meaningful outcomes for clients including Claude Code, GitHub Copilot, Cursor, Claude Code, OpenAI Codex, Kiro, DPaul Nyaga – Principal Software Engineer / AI & ML Engineering

• Senior Python / Software Engineering: Brings 10+ years building production Python, ML, and backend systems, with experience spanning application development, APIs, distributed services, performance optimization, and production deployment.

• Production AI / LLM Experience: Strong current hands-on experience with agentic AI, RAG, LangGraph/LangChain, OpenAI APIs, vector search, MCP/A2A agent protocols, evaluation, and guardrails. He has built production AI applications rather than only experimental or proof-of-concept solutions.

• Agentic AI & Quality Controls: Particularly well aligned with the role's AI-assisted development requirements. Paul has implemented bounded agent execution, attempt limits, timeouts, typed evidence contracts, deterministic tool calls, grounding checks, structured-output validation, and regression testing for LLM/RAG changes.

• Architecture / Full Lifecycle Ownership: Has designed FastAPI service boundaries separating deterministic application services from model-driven workflows and has built systems from architecture through deployment, monitoring, and production support.

• Cloud / DevOps: Hands-on experience across GCP and Azure with Docker, Kubernetes, CI/CD/MLOps, distributed systems, and production infrastructure. His current AI services are containerized and deployed using GCE/GKE and Kubernetes.

• Reliability & Observability: Strong production engineering background with LangSmith, Logfire, structured logging, tracing, performance monitoring, validation, and debugging across distributed AI services.