About the Role

Our partner is building an AI-first enablement team focused on evolving the enterprise architecture function through automation, lightweight applications, internal tooling, and generative AI. This is a hands-on engineering role for someone who can design, build, and ship practical software that saves time, improves governance workflows, and unlocks new capabilities.

The ideal candidate is first and foremost a strong software engineer: someone with deep Python experience, solid development fundamentals, good architectural judgment, and a clear understanding of database design, system design, testing, maintainability, and operational quality.

What You’ll Do

  • Partner directly with senior technologists and end users to understand workflows, pain points, and high-impact automation opportunities.
  • Design and build internal applications, APIs, dashboards, automations, agents, and reusable AI-enabled workflows.
  • Translate emerging GenAI usage, risks, and architectural patterns into practical governance tooling.
  • Use AI coding assistants such as Cursor, Claude, Codex, Amp, GitHub Copilot, or similar tools to accelerate delivery while maintaining engineering rigor.
  • Review, debug, refactor, and improve AI-generated code for correctness, architecture, security, maintainability, performance, and testability.
  • Design sound data models and data access patterns for internal applications and automation use cases.
  • Prototype quickly, demo frequently, and iterate based on user feedback without compromising core software quality.
  • Create reusable patterns, integrations, and guardrails that help others use AI-assisted development safely and productively.
  • Mentor and enable non-developers or technically adjacent stakeholders to build responsibly within appropriate guardrails.

Required Qualifications

  • Strong Development Foundations
  • Non-Negotiable 7-12 years of professional python engineering experience, with strong hands-on development depth.
  • Proven ability to design, build, debug, and operate production-quality software.
  • Strong understanding of software architecture, design patterns, modularity, testing, maintainability, and operational excellence.
  • Experience building APIs, services, automations, internal tools, or web applications using modern frameworks such as FastAPI, Flask, Airflow, or similar.
  • Solid understanding of database design, data modeling, SQL, data access patterns, and performance tradeoffs.
  • Ability to make sound architectural decisions and explain tradeoffs clearly.
  • Strong code review discipline, including the ability to identify brittle logic, poor abstractions, security concerns, scaling issues, and maintainability risks.

AI & Agent Technologies

  • 1-3+ years of hands-on experience applying modern GenAI technologies to real use cases.
  • Experience with LLM-based applications, AI agents, prompt engineering, RAG, workflow orchestration, or agentic systems.
  • Familiarity with modern AI frameworks, protocols, and platforms such as LangGraph, MCP, Agent SDKs, vector databases, retrieval pipelines, or similar technologies.
  • Up-to-date knowledge of the rapidly evolving AI landscape, including emerging models, coding agents, orchestration patterns, evaluation approaches, and development tooling.