Senior AI Engineer

You will be responsible for the technical vision and implementation of the AI algorithms that enable the copilot to understand, reason, and reliably answer users’ business-related questions.

You will work hand-in-hand with the other tech leads and product leads to define and execute the product’s overall technical strategy.

• Define and drive the AI strategy: design the technical roadmap around RAG, semantic search, language models (LLMs), agent orchestration (LangGraph, etc.), and answer quality.

• Lead and grow the team (MLEs, data scientists, data engineers): pair programming, code reviews, mentoring, hiring, and establishing best practices.

• Design and industrialize AI pipelines: ingestion, vectorization, indexing, fine-tuning, evaluation, and model monitoring.

• Strong understanding of LLM behavior, prompt-engineering techniques, and strategies for orchestrating multi-step AI agents

• Ability to connect AI agents with external tools, APIs, databases, and automation platforms to enable end-to-end workflow execution

• Experience designing and implementing agentic workflows, including task decomposition, tool integration, and autonomous decision-making logic.

• Proficiency in monitoring, evaluating, and optimizing agent performance, including error handling, memory management, and iterative refinement.

• Ensure the robustness and scalability of AI components, working closely with the platform/backend team.

• Collaborate with Product team across squads to turn business requirements into effective technical solutions.

• Conduct continuous technology watch: stay at the forefront of RAG, LLMOps, evaluation frameworks, agents, and multimodality.

What we expect from you

• You can switch easily between strategic and hands-on work: architect an AI system one day, and optimize a pipeline or model the next.

• You know how to balance delivery speed with technical quality.

• You can communicate clearly with both technical and non-technical stakeholders.

• You drive the adoption of best practices (testing, CI/CD, documentation, monitoring).

• You foster a strong culture of collaboration and feedback.

• You are comfortable in an agile environment (Scrum, squads, sprints, rituals).

Preferred experience

• Solid experience (5+ years) in Machine Learning / NLP / LLMs, including significant work on production-grade projects.

• Strong command of RAG & LLMOps concepts and tools: vector DBs, retrievers, embeddings, evaluation, LangChain/LangGraph, agent orchestration, etc.