Agentic Developer (LLM-Native / Enterprise)

Agentic Developer (LLM-Native / Enterprise)

This opportunity is for developers who are comfortable generating, refactoring, and evolving production-grade software using large language models as a primary development interface. Rather than adding AI features to products, you’ll help transform how enterprise software itself is built.

Our client is seeking Agentic Developers who combine deep engineering judgement with fluent command of LLM-driven development workflows. You’ll work on complex enterprise systems — often legacy platforms operating in highly regulated environments — modernising them with AI-native engineering practices while maintaining the reliability, auditability, and rigor these systems demand.
What You’ll Be Doing

You’ll operate as a developer who uses AI as a core development interface, not just a productivity tool.

Your responsibilities will include:
Generating, refactoring, and extending enterprise-grade codebases using LLMs as first-class development tools Modernising complex legacy systems using AI-driven development workflows Applying responsible practices within regulated industries such as financial services or capital markets Designing and guiding agentic development workflows, where LLMs reason, iterate, and generate production-ready code Validating and hardening AI-generated code to meet production, security, and audit standards Collaborating with architects, product managers, and stakeholders to turn ambiguous requirements into working systems quickly Helping enterprise teams adopt LLM-native software engineering practices at scale What Our Client Is Looking For

You’re an experienced engineer who understands both traditional enterprise development and modern AI-assisted workflows.

Essential experience includes:
Strong software engineering background working with enterprise or legacy systems Experience producing production-grade software using AI-assisted development approaches Experience working in mature CI/CD environments with automated testing pipelines Comfort operating in regulated or risk-aware environments Ability to reason about system behaviour, edge cases, and failure modes, even when code is AI-generated Fluency in at least one major enterprise language or ecosystem such as: Java C# Python Strong judgement around when to trust LLM outputs — and when not to Nice to Have

While not essential, it would be beneficial if you have:
Experience designing agentic development workflows Exposure to large-scale modernization programmes (monolith to services, legacy refactors, platform rewrites) Strong views on how software engineering should evolve in an LLM-first world

This role is hybrid 2/3 days onsite in Los Angeles.

Need to have financial experience to be considered.

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