Sr. Applied Scientist, Agentic Automated Reasoning Group

Amazon Amazon · Big Tech · Boston, MA · Applied Science

Sr. Applied Scientist role focused on building next-generation software verification tools by combining AI, cloud computing, and formal verification expertise. The role involves end-to-end technical leadership, identifying and applying AI techniques (like generative AI) for tasks such as requirement formalization, test generation, and proof repair, alongside traditional verification methods.

What you'd actually do

  1. End-to-end technical leadership for delivering AR solutions working backwards customer use cases.
  2. Identify tools and methods capable of addressing the verification needs of customers, including any novel analysis capabilities required.
  3. Use tools spanning from fuzzers, property-based testing to model checkers, and interactive theorem provers to establish program properties.
  4. Explore generative AI techniques to help customers formalize their requirements, find revealing tests, generate required boiler plate for testing and model checking, and find and repair program proofs.

Skills

Required

  • PhD in operations research, applied mathematics, theoretical computer science, or equivalent
  • Experience in formal verification, program analysis, constraint-solving, or theorem proving (academic or professional work)
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals

Nice to have

  • Experience in professional software development
  • Experience with interactive theorem provers, particularly Lean or Rocq
  • Knowledge of one or more methods of defining semantics: operational, denotational, axiomatic, etc.
  • Experience with automated software analysis techniques: abstract interpretation, data flow, model checking, etc.

What the JD emphasized

  • PhD, or Master's degree and 7+ years of applied research experience
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience in formal verification, program analysis, constraint-solving, or theorem proving (academic or professional work)

Other signals

  • combining advances in artificial intelligence, the computational capacity of the cloud, and our deep expertise in the domain
  • build new tools that solve code analysis problems previously considered beyond reach
  • Explore generative AI techniques to help customers formalize their requirements, find revealing tests, generate required boiler plate for testing and model checking, and find and repair program proofs.