Lead Agentic Strategy & Architecture

• Own the technical vision and architecture for agentic systems at Orakl: multi-step workflows integrating tools, memory and state management, planning, and human-in-the-loop controls.

• Stay at the forefront of the field — continuously monitor state-of-the-art agentic methods, evaluate their applicability to Orakl's context, and drive adoption of relevant innovations across the team.

• Design, ship, and operate production-grade agentic systems that answer key health challenges for cancer patients, including:

  • Scientist-facing agents that accelerate and improve scientific development workflows (Drug Screen Scoring, Sensitivity-Phenotype Profiling, Protein-Ligand Prediction, and more).
  • Data Quality Agents that continuously monitor and validate the integrity of data generated across our experimental and computational pipelines.
  • Product Agents embedded in our core product to support evidence-based therapeutic decision-making.

Engineering

• Contribute to the development of our flagship predictive oncology platform, by shipping high-quality software features in close collaboration with the engineering team.
• Productionize key models and pipelines (e.g., Sensitivity-Phenotype Profiling) to make them robust, scalable, and ready for use in scientific and commercial contexts.
• Influence ML infrastructure and hardware decisions to ensure training and inference workloads are scalable, reliable, and cost-efficient.

Who You Are

• A builder at heart — you thrive when you're shipping working systems, not writing perfect specifications.
• Deeply curious about the potential of LLMs and agentic AI, and excited to apply these technologies in a domain where they can genuinely improve health outcomes.
• A collaborative technical leader who enjoys raising the bar across teams through mentorship, clear technical communication, and well-reasoned architectural choices.
• Comfortable navigating ambiguity and operating at the frontier of a fast-evolving field, where the right answers often don't exist yet.
• Energized by working in a multidisciplinary environment alongside experimental scientists, clinicians, and product engineers.

Minimum Qualifications

• Master’s degree in a quantitative field (Computer Science, Mathematics, Engineering) and 3+ years of experience building production software, including meaningful hands-on experience deploying LLM-powered applications.
• Strong proficiency in Python and modern AI/ML tooling; familiarity with agentic frameworks (e.g., LangChain, LlamaIndex, Strands, or equivalent).
• Proven track record of taking AI systems from prototype to production, including testing, monitoring, and iteration in a real-world environment.
• Solid software engineering fundamentals: API design, data pipelines, version control, cloud infrastructure.
• Ability to influence technical direction through collaboration and constructive challenge, not just authority.

Preferred Qualifications

• Experience designing or operating multi-agent systems (tool use, memory, orchestration, human-in-the-loop).
• Exposure to healthcare, life sciences, or other regulated/high-stakes domains.
• Familiarity with ML infrastructure topics: distributed training, model serving, inference optimization, GPU workload management.
• Prior experience working in early-stage startups or fast-growing deep tech environments.
• Contributions to open-source projects or publications related to LLMs, agentic AI, or applied ML

Recruitment process

1. HR Call — Getting to know each other, aligning on expectations and context.
2. Technical Deep Dive — A deep conversation on your past AI engineering work: architecture decisions, production challenges, and lessons learned.
3. Technical Case — A system design exercise centered on agentic AI, representative of the real problems you'll face at Orakl.
4. Reference Call — A conversation with one or two people you've worked with closely.
5. Founder Interview — A final discussion with our founders on vision, culture fit, and mutual ambitions.