The RoleAt RoZetta, AI agents write most of our code. We are looking for an engineer to design the system those agents work in: the skills, the architecture, the tests and the evals that turn agent output into production software for global financial markets.

• What you will do:Deliver features end to end by orchestrating teams of AI coding agents: orchestrators, parallel workers, reviewers and evaluators.
• Design and maintain the agent skills, context, tools and MCPs that every engineer and agent on the team uses.
• Characterise systems before you change them: boundaries, data flows, invariants and failure modes.
• Set the architecture principles and design patterns our agent teams follow: modular design, clear contracts, domain-driven design.
• Build the tests and evals that let agents move fast safely, and make CI the gatekeeper.
• Build AI features into our products, with evals, tracing and cost measured from day one.
• Work with our Forward Deployed Engineers to turn client solutions into reusable platform capability.
• Help the team make the shift by pairing, reviewing and sharing what works.

• You are a good fit if you have:Senior full-stack engineering background with real data depth: Python, JavaScript, SQL, data modelling and AWS. Ideally, some exposure to building production data pipelines or to data governance (quality, lineage, access control).
• Shipped production software substantially built by AI agents, and can show us the workflow, the guardrails and where it breaks.
• Strong systems thinking: you can map an unfamiliar system (its boundaries, data flows and failure modes) and explain what you would change and why. You have owned system architecture: modular systems, contracts and trade-offs.
• A real testing discipline. Your tests have caught what agents got wrong.
• A habit of starting things nobody asked for, and finishing them.

• Nice to haveDesigned agent skills, prompts or tooling that other engineers use
• LLM evals and tracing for AI features using Langfuse
• Security for agents working near sensitive data
• Iceberg, ClickHouse or Spark; React; Kubernetes
• Financial markets or financial data

• Why RozettaWork agent-first, on a platform designed for it.
• Real ownership. Your patterns become how the whole team builds.
• Hard, interesting problems in global financial data.
• 
  

The RoleAt RoZetta, AI agents write most of our code. We are looking for an engineer to design the system those agents work in: the skills, the architecture, the tests and the evals that turn agent output into production software for global financial markets.

• What you will do:Deliver features end to end by orchestrating teams of AI coding agents: orchestrators, parallel workers, reviewers and evaluators.
• Design and maintain the agent skills, context, tools and MCPs that every engineer and agent on the team uses.
• Characterise systems before you change them: boundaries, data flows, invariants and failure modes.
• Set the architecture principles and design patterns our agent teams follow: modular design, clear contracts, domain-driven design.
• Build the tests and evals that let agents move fast safely, and make CI the gatekeeper.
• Build AI features into our products, with evals, tracing and cost measured from day one.
• Work with our Forward Deployed Engineers to turn client solutions into reusable platform capability.
• Help the team make the shift by pairing, reviewing and sharing what works.

• You are a good fit if you have:Senior full-stack engineering background with real data depth: Python, JavaScript, SQL, data modelling and AWS. Ideally, some exposure to building production data pipelines or to data governance (quality, lineage, access control).
• Shipped production software substantially built by AI agents, and can show us the workflow, the guardrails and where it breaks.
• Strong systems thinking: you can map an unfamiliar system (its boundaries, data flows and failure modes) and explain what you would change and why. You have owned system architecture: modular systems, contracts and trade-offs.
• A real testing discipline. Your tests have caught what agents got wrong.
• A habit of starting things nobody asked for, and finishing them.

• Nice to haveDesigned agent skills, prompts or tooling that other engineers use
• LLM evals and tracing for AI features using Langfuse
• Security for agents working near sensitive data
• Iceberg, ClickHouse or Spark; React; Kubernetes
• Financial markets or financial data

• Why RozettaWork agent-first, on a platform designed for it.
• Real ownership. Your patterns become how the whole team builds.
• Hard, interesting problems in global financial data.
•