Applied AI Engineer, Beneficial Deployments

Anthropic Anthropic · AI Frontier · Bangalore, India · Sales

Applied AI Engineer role focused on deploying AI to mission-driven organizations, advising on evals and agent architectures, building ecosystem tooling, and prototyping new agents. Requires production experience with LLM applications and a builder mindset.

What you'd actually do

  1. Serve as a deep technical partner to mission-driven organizations through advising on evals, agent architectures, context engineering, cost optimization, and more
  2. Provide hands-on support to partner engineering teams through pair programming, prototyping, and code contributions that accelerate their development
  3. Develop public goods infrastructure that benefits entire ecosystems through benchmarks, MCP’s, and Agent Skills
  4. Identify challenges unique to social impact partners, and contribute findings and improvements back to product, engineering, and research
  5. Create technical presentations, demos, and scalable technical content (documentation, tutorials, sample code) to accelerate partner adoption and self-service

Skills

Required

  • 8+ years as a Software Engineer, Forward Deployed Engineer, or technical founder
  • Production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale
  • Experience working in ed-tech, healthcare, scientific research, nonprofit, or other mission-driven organizations

Nice to have

  • A love of teaching, mentoring, and helping others succeed
  • A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission

What the JD emphasized

  • Production experience building LLM-powered applications
  • Builder credibility that earns trust with technical founders and engineering teams—you've shipped products and can speak from experience

Other signals

  • building ecosystem-level tooling and infrastructure
  • prototyping new agents
  • advising on evals
  • production experience building LLM-powered applications