Senior Product Manager, Technical - Life Sciences, Amazon Bio Discovery

Amazon Amazon · Big Tech · Seattle, WA · Project/Program/Product Management--Technical

The Senior Product Manager, Technical will lead product development for AI-driven protein design and antibody engineering, defining generative AI agent-based experiences to accelerate drug discovery. This role involves integrating computational design pipelines with laboratory workflows and creating efficient systems for rational therapeutic design, requiring a strong technical background and experience with ML/AI technologies in life sciences.

What you'd actually do

  1. lead pioneering product development for AI-driven protein design and antibody engineering
  2. define novel, generative AI agent based experiences to help researchers accelerate drug discovery
  3. drive innovation by integrating computational design pipelines with laboratory workflows
  4. creating efficient systems for rational therapeutic design
  5. defining key product directions, adopting or inventing new machine learning techniques, reimagining user workflows and experiences, and fundamentally changing the state of practice

Skills

Required

  • 6+ years of working as a Technical Product Manager experience
  • 5+ years of technical (software development, network development, IT, other related) experience
  • Experience delivering large-scale SaaS, PaaS or LaaS products where you are responsible for the full product lifecycle, from concept through GTM (go to market)

Nice to have

  • Advanced degree (MS or PhD) in Computational Biology, Bioinformatics, Structural Biology, or related field, or equivalent industry experience
  • Demonstrated understanding of protein structure prediction and design tools (e.g., AlphaFold, RFDiffusion, ProteinMPNN)
  • Experience with drug discovery workflows and therapeutic development processes, particularly in antibody development
  • Track record of successful product launches that leverage ML/AI technologies
  • Strong technical background with ability to evaluate emerging technologies and contribute to technical discussions around computational biology
  • Experience leading cross-functional teams and collaborating with research scientists, engineers, and business stakeholders
  • Proven ability to translate complex scientific concepts into clear product requirements and user experiences

What the JD emphasized

  • lead pioneering product development
  • define novel, generative AI agent based experiences
  • integrating computational design pipelines with laboratory workflows
  • rational therapeutic design
  • adopting or inventing new machine learning techniques
  • reimagining user workflows and experiences
  • fundamentally changing the state of practice
  • building scalable end user products
  • Demonstrated understanding of protein structure prediction and design tools
  • Experience with drug discovery workflows and therapeutic development processes
  • Track record of successful product launches that leverage ML/AI technologies
  • Proven ability to translate complex scientific concepts into clear product requirements and user experiences

Other signals

  • generative AI agent based experiences
  • accelerate drug discovery
  • integrating computational design pipelines with laboratory workflows
  • rational therapeutic design
  • adopting or inventing new machine learning techniques