Senior AI Engineer Leader

freeC's Client

• Take ownership of the full research-to-production cycle for our agent: explore new agentic methods, run structured experiments, and implement what delivers real results.
• Continuously improve the agent’s core capabilities — including planning, tool usage, reasoning, memory, and multi-agent coordination — based on real task performance and benchmark results, not demos.
• Build and maintain an evaluation framework to accurately measure whether changes lead to real improvements. This is a critical part of the role.
• Identify where the agent breaks down at its limits and design solutions to address those gaps.
• Contribute to leading the agent platform team by setting technical direction, mentoring peers, reviewing work, and raising overall engineering standards.
• Turn cutting-edge research into practical engineering decisions while balancing reliability, latency, and cost constraints.

Requirements

• PhD in Computer Science, Machine Learning, Artificial Intelligence, or a highly quantitative field, with a focus on autonomous systems or NLP.
• Strong senior-level experience building production-grade agent systems — including real planning, tool usage, and multi-step reasoning (not just prompt-based pipelines). Depth of experience matters more than job title or exact years (typically ~6+ years in software/ML or equivalent hands-on research and deployment experience).
• Proven ability to take ideas from research and successfully implement them in production, with measurable impact.
• Deep understanding of how agent systems operate — including tool design, state and context handling, orchestration, and multi-step workflows — along with the judgment to choose or build the right approach. (Frameworks like LangGraph or MCP are just tools, not the core skill.)
• Strong focus on evaluation: experienced in building testing frameworks for non-deterministic systems and making decisions based on data rather than intuition.
• Able to read and break down ML and agent-related research papers effectively; solid Python skills and strong system design fundamentals.
• Good judgment and communication skills to help guide a technical team — setting direction, reviewing work, and raising standards — even without a formal leadership title.

Nice to have

• Experience working in scientific or research-driven environments, especially in areas like drug discovery or other iterative experimental workflows.
• Previous experience mentoring others or contributing to technical direction within a small team.
• Background in RAG systems, memory architectures, or multi-agent systems; familiarity with biology or chemistry is a plus.

• Opportunity to build a strong professional network through collaboration with pharmaceutical companies, industry experts, and academic partners.
• Work on meaningful projects that tackle important challenges in drug discovery and healthcare.
• Enjoy 2 work-from-home days per month and daily company-provided lunch.
• Receive holiday and Tet bonuses, along with performance-based incentives.
• Full social insurance coverage based on total salary.