Senior AI Engineer_CNTR

About the role

This is a Senior AI Engineer role owning a finance domain end-to-end — from context engineering and prompt design through tool use, evals, guardrails, and the UX around them — working directly with controllers, accountants, and CFOs to understand workflows and replace manual processes with production-grade agent systems. This is a backend-heavy, full-stack-in-practice role: no PM writes your specs and no architecture committee gates your ideas. The hardest problems on the roadmap involve building AI agents that finance teams and auditors can trust, giving agents the right financial context over large and messy data, and orchestrating durable workflows across flaky enterprise systems.

Responsibilities

• Own a finance domain end-to-end, building the agent system that automates it across context, prompts, tools, evals, guardrails, and UX, working directly with controllers and CFOs
• Design and implement durable, replay-safe orchestration for long-running AI workflows across flaky, stateful enterprise systems
• Build the trust layer for non-deterministic systems: evals, verification, guardrails, and observability that catch agent mistakes before a human does
• Ship full-stack when the work calls for it, owning decisions across the LLM pipeline, infrastructure, backend, and UX within your pod
• Build idempotent, audit-ready write-back systems for ERPs and financial systems with full traceability
• Own serious context engineering: retrieval, memory, and tool design that gets agents to reason reliably over large, messy, proprietary financial data

Requirements

• 2+ years specifically building and shipping AI agents for real-world, production problems; can point to something live and explain how you made it reliable
• 4+ years of software engineering experience, mostly backend or infrastructure
• Research grounding in AI agents, LLMs, or machine learning, ideally peer-reviewed work at top venues (NeurIPS, ICML, ICLR, ACL, or similar)
• Strong backend proficiency in a modern language; Python is the primary stack
• Worked at an early-stage startup (pre-seed through Series B)
• Able to work in-person at the New York City office on the stated schedule (6 days a week, 9am-7/8pm)

Qualifications

• Nice to have: Experience in fintech, ERP, accounting, payments, banking, treasury, audit, or compliance software
• Shipped agents that take real action on production systems (money movement, ledger writes, system-of-record updates) with safety, idempotency, and rollback as first-class concerns
• Built trust layers for non-deterministic systems: evals, verification, guardrails, and observability in production
• Deep context engineering experience: retrieval, memory, and tool design over large, messy, proprietary data

Skills

• Experience with AI agents, LLMs, or machine learning
• Backend proficiency in a modern language (Python preferred)
• Experience with context engineering and retrieval, memory, and tool design
• Experience with building trust layers for non-deterministic systems
• Experience with orchestrating durable workflows across flaky, stateful enterprise systems
• Experience with building and shipping AI agents for real-world, production problems

Benefits

None available

Pay

Details will be provided upon interview

Schedule

Startup hours, 6 days a week, 9am to 7pm or 8pm

Visa & work authorization

None available