2 месяца назад
AI Product Engineer
115 000 - 130 000GBP
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Product Engineer (LLM/Agentic Systems): Building reliable AI infrastructure, natural-language approval workflows, and an intelligent collections agent for a revenue platform with an accent on production-grade LLM systems, deterministic business logic, and resilient backend engineering. Focus on designing agentic workflows, evaluation infrastructure, secure multi-provider AI systems, and recovery from partial failures in revenue-critical infrastructure.
Location: London, UK; hybrid with three days per week in the office
Salary: £115,000–£130,000 per year, plus equity
Company
is building an AI-powered revenue platform for finance teams, covering quoting, billing, and revenue recognition.
What you will do
- Build and own AI infrastructure for reliable software on top of non-deterministic models, including agentic workflows, tools, prompt iteration, and evaluations.
- Develop AI-powered approval workflows that convert natural-language customer rules into deterministic and auditable business logic.
- Build an intelligent collections agent that autonomously manages reminders, escalations, and payment-collection workflows.
- Design and ship production backend systems with strong reliability, security, monitoring, and recovery from partial failures.
- Work end-to-end with product, design, and customers to identify, build, ship, and support business-critical features.
- Contribute to architecture and engineering practices as the team grows.
Requirements
- Experience shipping LLM-based systems to real customers and understanding their production failure modes.
- Experience designing agentic systems using components such as embeddings, memory, tool use, long-running state, and failure recovery.
- Experience building evaluation infrastructure, including datasets, LLM-as-judge systems, prompt regression tests, and monitoring.
- Production backend engineering experience and a strong focus on reliability for business-critical systems.
- Understanding of AI security, multi-provider AI tooling, and secure operation of models treated as untrusted by default.
- Clear communication, customer focus, ownership, and comfort working in an ambiguous, fast-moving environment with on-call responsibility.
Nice to have
- Experience with Kotlin, Http4k, Spring Boot, Exposed, Result4k, Postgres, BigQuery, Vertex AI, LangSmith, Google Cloud Pub/Sub, Terraform, TypeScript, or React.
- Experience working in an early-stage product engineering team.
Culture & Benefits
- Small, cross-functional engineering organization with significant ownership and influence over architecture.
- Three office days per week and team lunches on Wednesdays.
- Meaningful share options.
- 25 days of holiday plus bank holidays.
- Flexible pension through Penfold with salary sacrifice available.
- Visa sponsorship available.
Hiring process
- The process typically takes approximately two weeks from start to finish.
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