Senior Aws Forward Deployed Engineer - Gps

Senior AWS Forward Deployed Engineer focused on building and deploying GenAI-enabled solutions and agentic platforms for enterprise clients. The role involves translating business needs into AI solutions, developing scalable AI engineering patterns, and applying architecture decisions for quality, safety, latency, cost, and model risk. Requires strong software engineering practices, experience with AWS (Bedrock, Bedrock Agents, Knowledge Bases, Guardrails), and client-facing engagement.

What you'd actually do

  1. Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  2. Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  3. Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  4. Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  5. Apply architecture decisions that balance quality, safety, latency, cost, and model risk.

Skills

Required

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering.
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS including hands on experience with one of the following key platform technologies; Amazon Bedrock, Bedrock Agents, Knowledge Bases, Guardrails
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
  • Ability to obtain and maintain a US government security clearance

Nice to have

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures
  • Experience operating within hybrid onshore/offshore teams
  • Familiarity with security, privacy, and compliance considerations

What the JD emphasized

  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS including hands on experience with one of the following key platform technologies; Amazon Bedrock, Bedrock Agents, Knowledge Bases, Guardrails

Other signals

  • GenAI-enabled solutions
  • agentic platforms
  • human-in-the-loop controls
  • production-quality code
  • LLM-powered solutions