About The Position

Lab49 is looking for Agentic Developers, engineers who don’t just use AI tools but write software through them. This is not a role focused on “adding AI features” or “building AI platforms.” Instead, we are seeking developers who generate production‑grade enterprise code using large language models as a primary interface, particularly while modernizing or extending complex, legacy systems in highly regulated environments. You will operate as a vibe coder in the best sense of the term: combining deep engineering intuition, strong system design instincts, and fluent command of LLMs to move faster than traditional development workflows- without compromising rigor, compliance, or reliability.

Requirements

  • Strong software engineering background with experience in enterprise or legacy systems
  • Hands-on experience manufacturing production-grade software in AI-assisted way at scale (not just autocomplete or chat usage, but sustained code production through prompts, agents, or workflows)
  • Experience working within mature CI/CD environments, with automated testing fully integrated into the delivery pipeline
  • Comfort working in regulated, risk‑aware environments, where correctness, explainability, and traceability matter
  • Ability to reason about system behavior, edge cases, and failure modes- even when the code is AI‑generated
  • Fluency in at least one major enterprise language or ecosystem (e.g., Java, C#, Python, JVM‑based stacks, etc.)
  • Strong intuition for when to trust the model- and when not to
  • Leading teams through the AI adoption journey and helping enterprises build scalable, robust AI software factory frameworks

Nice To Haves

  • Experience designing or using agentic development workflows (multi‑step prompting, tool‑using agents, code‑generation loops)
  • Exposure to modernization programs (monolith → services, legacy refactors, platform rewrites)
  • Opinions about how software engineering should evolve in an LLM‑first world - and the ability to defend them

Responsibilities

  • Generate, refactor, and extend enterprise‑grade codebases by orchestrating LLMs as first‑class development tools, not just assistants
  • Modernize and evolve legacy systems (often written in traditional enterprise stacks) using AI‑driven development workflows
  • Apply “vibe coding” practices responsibly within highly regulated domains such as financial services, capital markets, or other compliance‑heavy environments
  • Design and guide agentic workflows where LLMs reason, iterate, and produce code aligned with business and architectural constraints
  • Validate, test, and harden AI‑generated code to meet production, security, and audit standards
  • Collaborate closely with product managers, architects, and clients to translate ambiguous requirements into working systems - fast
  • Influence how Lab49 and its clients adopt LLM‑native software engineering practices at scale
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