Amazon
Senior Security Engineer, Forward Deployed Engineering, AWS Forward Deployed Engineering
$175K–$248K
Boston, MA +5 · Senior · Full-time · Posted Sep 17, 2026
- Location
- Boston, MA
Seattle, WA
Arlington, VA
New York, NY
Mountain View, CA
Dallas, TX - Experience
- 5+ years in specified security areas and 5+ years identifying risks and developing mitigations; 4+ years non-internship programming and security code review.
- Visa sponsorship
- The selected candidate must be a US Citizen.
About the job
Secures production AI systems deployed in customer environments by embedding with AWS Forward Deployed Engineering teams and building security controls and reusable tooling.
What you'll do
- Review AI system designs, model threats, and implement security controls in customer environments.
- Build reusable security automation and integrate security into engineering workflows.
- Respond to production security incidents and document reusable patterns and guidance.
What they ask for
- 5+ years in a combination of application security, identity and access controls, incident response, mobile security, cloud security, AI security, threat intelligence, or penetration testing.
- 5+ years identifying security issues and risks and developing mitigation plans.
- 4+ years of non-internship scripting, programming, and security code review experience.
- Knowledge of at least two of Scala, Java, Python, C/C++, or Go; threat modeling and penetration testing experience, or equivalent stated analytical, detail, and communication strengths.
Nice to have
- Experience with security in service-oriented architectures/microservices and web services.
- Experience with PCI DSS, ISO 27001, HIPAA, NIST, AWS technologies, or a US government security clearance of top secret or above; alternatively, 7+ years of IT platform implementation in a technical and analytical role.
Pay
USD 183,000.00 - 247,600.00 annually (base salary); USD 178,400.00 - 226,700.00 annually (base salary); USD 175,100.00 - 236,900.00 annually (base salary)
Tools
Scala, Java, Python, C/C++, Go, Terraform, Bedrock, AWS
AI focus
Secures AI/ML pipelines and production AI systems, addressing threats such as prompt injection, guardrail bypass, model endpoint risks, training data protection, output filtering, and data isolation.
Model-written summary · the original posting is authoritative