AI Lead / Engineering Manager

New

UsersnapAI SaaS

Location: Remote, EuropeFull-TimeManager

Salary not disclosed

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Job Details

Experience: 7+ years of software engineering experience; ideally 2-3 years of people leadership.
Required Skills: DockerSQLFull Stack DevelopmentCI/CDSoftware EngineeringPrompt EngineeringLangChain

Have 7+ years of software engineering experience.
Have shipped AI features to production and owned their lifecycle from problem framing through post-launch iteration.
Bring hands-on technical leadership and experience leading delivery for a small team; 2-3 years of people leadership is ideal.
Demonstrate full-stack fundamentals across frontend, backend, and infrastructure.
Have practical experience with LLM APIs, prompt engineering, RAG, or similar techniques in live systems.
Use logging, monitoring, tracing, strong test coverage, automated testing, and evaluation of AI behavior.
Bring solid SQL and schema-design skills, and the ability to design scalable data pipelines and systems.
Define success metrics, design experiments, run offline and online evaluations, and use results to make decisions.
Have Docker fluency and CI/CD experience, with good practices for versioning prompts, models, and datasets.
Have experience integrating multiple LLM providers, working with vector databases, and using LangChain or a similar tool.
Have security and compliance experience, or a strong interest in those areas.

Own coordination, delivery timelines, workload allocation, and project follow-through for a small engineering team.
Break down ambiguous goals, sequence work with Product, flag slippage early, and ensure commitments are met.
Provide technical feedback in code reviews, design discussions, and 1:1s, and raise team standards.
Assess engineering practices and establish standards for observability, testing, security, architecture, and timeboxing.
Steward architecture decisions, including model selection and integration approach, balancing quality, cost, and latency.
Identify technical risks, especially those involving AI reliability, cost, and edge-case behavior.
Design, build, and ship AI-powered features from prototype through production.
Work with LLMs, embeddings, and related AI tooling to solve product problems.
Partner with Product on requirements and priorities and with company leadership on technical planning, resourcing, and sequencing.

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