Senior AI Engineering Lead (PhD)

A cutting-edge AI/ML company operating at the intersection of artificial intelligence and scientific research, focused on advancing drug discovery and healthcare through autonomous agentic systems. The team runs a production AI agent that orchestrates 300+ scientific tools, supported by a small, high-caliber engineering team. The company collaborates closely with pharmaceutical companies, industry leaders, and academic experts to address critical challenges in life sciences.

We are seeking a Senior AI Engineering Lead who combines the research depth of a scientist with the instincts of a technical leader. You will treat our production AI agent as a living research problem — continuously surveying the frontier of agentic AI, running structured experiments, and shipping what proves out in production with measurable evidence of improvement. The agentic field evolves rapidly, and we need someone with the taste to separate signal from hype, the ability to prototype promising ideas quickly, and the discipline to land only what holds up under real reliability, latency, and cost constraints.

You will own the full research-to-production loop for our agent: continuously upgrading core capabilities including planning, tool selection and reasoning, memory, and multi-agent coordination — measured against real tasks and benchmark outcomes, not demos. A critical part of the role is building and owning the evaluation harness that determines whether a change is genuinely an improvement. For a system answerable to scientific experiments, rigorous evaluation is the backbone of the work.

Beyond individual contribution, you will help lead the agent platform team — setting technical direction for agentic practices internally, mentoring engineers, reviewing work, and raising the quality bar across the team. You will also diagnose where the agent fails at the edge of its current capability and design targeted fixes, translating frontier research into pragmatic engineering decisions under production constraints.

• PhD in Computer Science, Machine Learning, Artificial Intelligence, or a highly quantitative field with a strong focus on autonomous systems or NLP

• Senior track record building production agentic systems — real planning, tool use, and multi-step reasoning, not prompt pipelines; depth counts more than title or tenure (roughly 6+ years of software/ML work, or equivalent research-and-shipping depth)

• Demonstrated ability to take a technique from current research and land it in a production system with measured impact

• Deep command of how agents actually work — tool definition, state and context management, orchestration, multi-step control — and the judgment to choose or build the right pattern

• Rigorous about evaluation: experience designing eval harnesses for non-deterministic systems and trusting data over intuition

• Fluent in reading and critically analyzing ML/agent papers; strong Python and system-design fundamentals

• The judgment and communication skills to help lead a technical team — set direction, review others' work, and raise the bar

Nice to Have:

• Exposure to scientific or research workflows, ideally drug discovery or another iterative experimental loop

• Prior experience mentoring or setting technical direction for a small team

• Background in RAG, memory systems, or multi-agent orchestration; bio/chem familiarity a plus

• Competitive salary, negotiable based on experience

• Opportunity to build a professional network through collaborations with pharmaceutical companies, industry leaders, and academic experts

• Work on impactful projects addressing critical challenges in drug discovery and healthcare

• 2 work-from-home days per month

• Daily lunch provided by the company

• Holiday and Tet bonuses; performance-based bonus

• Social insurance contribution on full salary