Amazon
Forward Deployed Engineer, Forward Deployment Engineering
$144K–$224K
Boston, MA +3 · Full-time · Posted Oct 20, 2026
- Location
- Boston, MA
Seattle, WA
New York, NY
East Palo Alto, CA - Experience
- 3+ years of non-internship professional software development; 2+ years in an Agile, startup, or rapidly scaling environment.
- Education
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
About the job
Embeds with enterprise customers to build, deploy, and operate AI-powered production systems and deliver customer outcomes.
What you'll do
- Translate customer needs into technical designs and build production AI applications and agentic workflows.
- Own workstream delivery across design, coding, testing, deployment, operations, and maintenance; resolve production issues and improve system reliability.
- Mentor teammates, support customer adoption, and develop reusable deployment patterns; requires 30–50% travel.
What they ask for
- 3+ years of non-internship professional software development experience.
- 2+ years working in an Agile, startup, or rapidly scaling environment.
- Experience communicating technical concepts to technical and non-technical audiences.
- Experience with agentic and spec-driven development and AI tools, including eval frameworks, agent tooling, RAG pipelines, and prompt engineering.
Nice to have
- Experience building or deploying AI/ML applications in production and/or working in customer production environments.
- Prior experience with React, TypeScript, Python, and/or Go; customer-facing technical project experience and AWS services experience are also listed.
Pay
USD 165,200.00 - 223,600.00 annually (base salary); USD 143,700.00 - 194,400.00 annually (base salary); USD 158,100.00 - 213,800.00 annually (base salary); USD 143,700.00 - 194,400.00 annually (base salary)
Tools
React, TypeScript, Python, Go, AWS, RAG pipelines
AI focus
Build and operate production AI applications and agentic workflows, integrating foundation models, customer data, and existing applications; use evaluations, guardrails, and prompt engineering.
Model-written summary · the original posting is authoritative