Senior AI Engineer – Global Commercial Services

This is a fully remote position, open to applicants in North Carolina.

📋 Description

• Develop end-to-end production agentic AI services, encompassing event triggers, LLM reasoning, and the delivery of persistent, surfaced results.

• Contribute to the collaborative agent framework, which includes orchestration, tool utilization, structured generation, and observability.

• Create RAG and embedding pipelines utilizing vector search within the operational database.

• Implement evaluations for new agent behaviors to inform prompt modifications.

• Design for reliability by classifying failures, ensuring idempotency, managing DLQ, and executing safe AI-feature rollouts.

• Engage in technical design discussions and code reviews, progressing towards ownership of design responsibilities.

• Assist in onboarding engineers to the AI stack.

• Collaborate across TypeScript and Go services, gRPC and tRPC APIs, Kafka, SQS, Lambda, EKS on AWS, feature-flagged rollouts, and infrastructure as code.

⛳️ Requirements

• Over 4 years of experience in building backend or distributed systems in a production environment.

• Delivered LLM-powered features, including prompts, retrieval, output management, and related model-call systems.

• Proficiency in either TypeScript or Go, with a willingness to work across both languages.

• Strong foundational knowledge of distributed systems, including queues, event-driven design, and failure mechanisms.

• An inquisitive mindset regarding the decision-making processes of an LLM versus those dictated by code.

• Effective communication skills across engineering, product, and design teams.

• Experience in building or managing internal platform tools or frameworks (preferred).

• Familiarity with writing LLM evaluations or utilizing LLM observability tools (preferred).

• Experience with durable execution or workflow orchestration engines, such as Temporal (preferred).

• AI features developed within financial services or other regulated sectors (preferred).

• Proven experience with vector search or embedding pipelines in a production setting (preferred).

🏝️ Benefits

• Bonus

• Benefits