Senior Agentic Developer, LLM‑Native / Enterprise, NY

What You’ll Do

Continuously experiment with emerging AI tools, development techniques, and agentic workflows to accelerate delivery and improve client outcomes.

Partner with clients to turn innovative AI capabilities into practical, production-ready solutions that create measurable business value.

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.

What We’re Looking For

Strong engineering fundamentals coupled with real-world experience solving difficult production problems ("battle scars") in enterprise systems

A passion for continuous learning, experimentation, and achieving results with clients.

Hands-on experience manufacturing production-grade software in an 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.

Interest in growing toward a Forward Deployed Engineering (FDE) style profile, combining technical excellence, customer engagement, and outcome-driven delivery.

Nice to Have

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