AI Lead – Engineering Manager

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

📋 Description

• Lead a compact engineering team focused on delivering AI-enhanced Usersnap product functionalities.

• Establish a consistent delivery rhythm through shared objectives, achievable timelines, visible workload, and thorough project follow-through.

• Evaluate the codebase, tools, and practices while defining engineering standards for observability, testing, security, compliance, and architecture.

• Deliver AI-driven features from initial prototype to production.

• Manage team workload, timelines, sequencing, and delivery commitments.

• Provide technical insights through code reviews, design discussions, and one-on-one meetings.

• Enhance team capabilities and optimize the use of AI tools without compromising quality.

• Take ownership of architecture decisions, including model selection, integration strategies, and quality/cost/latency considerations.

• Identify technical risks associated with AI reliability, cost, and edge-case behaviors.

• Engage hands-on with LLMs, embeddings, and relevant AI tools.

• Develop across the stack with tested, monitored, and maintainable implementations.

• Collaborate with Product on requirements and priorities.

• Work alongside company leadership on technical planning, resource allocation, and sequencing.

⛳️ Requirements

• Over 7 years of experience in software engineering.

• Ideally possess 2–3 years of leadership experience in roles such as tech lead, engineering manager, or player-coach.

• Proven experience in deploying AI features to production and managing their lifecycle from problem identification to post-launch iterations.

• Strong full-stack fundamentals in frontend, backend, and infrastructure.

• Practical experience with LLM APIs, prompt engineering, RAG, or similar techniques in operational systems.

• Rigor in observability and testing, including logging, monitoring, tracing, robust test coverage, automated testing, and assessment of AI behavior.

• Solid understanding of SQL and schema design.

• Ability to design scalable data pipelines and systems.

• Experience in defining success metrics, designing experiments, and conducting both offline and online evaluations.

• Proficient in Docker, CI/CD, and versioning for prompts, models, and datasets.

• Experience in integrating multiple LLM providers and working with vector databases.

• Familiarity with LangChain or similar tools.

• Comfortable with fine-tuning models when necessary.

• Experience or strong interest in security and compliance.

• Ability to timebox AI development work and meet deadlines.

• Capable of independently identifying challenges and proposing solutions.

• Comfortable taking ownership of results in a lean team environment.

🏝️ Benefits

• Enjoy the flexibility of 100% remote work from any location at any time.

• Work in a flexible and autonomous environment.

• Benefit from minimal bureaucracy and sustainable meeting practices.

• Join a small, friendly team atmosphere.

• Access to an internal SaaS professional network for sharing ideas, knowledge, learning, and expertise.

• Take advantage of flexible time off.