Note: The job is a remote job and is open to candidates in USA. General Dynamics Information Technology (GDIT) is hiring a Senior AI Engineer to design, build, and deploy secure AWS AI solutions for the NIAID research community. The role focuses on production generative AI and agent systems, AWS architecture and operations, and collaboration with technical teams and stakeholders.
Responsibilities
- Design, build, and ship autonomous and multi-agent systems in production using Amazon Bedrock and Bedrock AgentCore — covering tool use, orchestration, memory, identity, and human-in-the-loop patterns
- Select, evaluate, and integrate foundation models on Amazon Bedrock; design, implement, and evaluate RAG pipelines (including retrieval quality and RAG evaluation); apply prompt engineering and model customization
- Design highly available, scalable, secure AI architectures on AWS, applying the Well-Architected Framework and generative-AI best practices. Contribute to the overall AI strategy, reference architectures, and reusable accelerators
- Operationalize AI agents end-to-end — automated agent evaluation, guardrails, observability, cost and latency optimization, CI/CD, and Infrastructure as Code (Terraform or CloudFormation). Own the reliability, quality, and performance of deployed agents
- Implement responsible-AI guardrails, data privacy, and security controls (Amazon Bedrock Guardrails, IAM, encryption, PII handling) and ensure compliance with relevant frameworks
- Communicate clearly with technical and non-technical stakeholders; mentor junior engineers; and stay current with the fast-moving AWS AI landscape
- Architect, implement, and evolve AWS cloud solutions supporting generative AI application architectures, including Amazon Bedrock, multimodal LLMs, Retrieval-Augmented Generation (RAG), vector search, knowledge integration, agentic capabilities, and distributed cloud AI services
- Partner with application developers, AI engineers, security teams, and stakeholders to translate requirements into scalable, well-architected cloud platform solutions
- Engineer full-stack AWS solution plumbing to support production GenAI applications
- Serve as a senior technical resource and customer-facing advisor — mentoring engineers, communicating tradeoffs, and presenting recommended AI approaches to technical and non-technical stakeholders
Skills
- AI Agents, AI Prompting, Amazon Bedrock, AWS Bedrock AgentCore, Generative AI
- 8 + years of related experience
- Bachelors in Computer Science, AI/Data Science, Engineering (or equivalent practical experience)
- 8+ years of relevant experience
- Proven experience designing, building, and running AI agents or generative AI applications in production — not only prototypes or notebooks
- Hands-on experience with the AWS AI/ML stack: Amazon Bedrock, Bedrock AgentCore, Amazon SageMaker, and Amazon Q
- Solid command of generative AI and agentic concepts: foundation models, prompt engineering, RAG and RAG evaluation, vector databases, tool/function calling, multi-agent orchestration, memory, and agent evaluation
- Practical experience with at least one agent framework (Strands Agents, LangGraph, LangChain, CrewAI, or the Bedrock Agents SDK)
- Experience with Infrastructure as Code (Terraform, CloudFormation, or AWS CDK) and CI/CD pipelines for deploying AI/ML workloads
- Deep hands-on AWS experience across compute, networking, storage, identity, security, monitoring, and APIs, with experience designing scalable, resilient, secure architectures
- Experience with DevOps/CI-CD practices, containerization (Docker), and operational support
- Strong architecture, troubleshooting, consulting, and communication skills, with demonstrated ability to independently own complex solutions and collaborate across technical and non-technical stakeholders
- Strong Python proficiency with solid software engineering practices (version control, testing, code review)
- Ability to obtain and maintain a Public Trust
- Well-Architected Framework and GenAI reference-architecture / reusable-accelerator experience
- LLMOps/MLOps tooling (model evaluation, observability, prompt management, guardrails)
- Fine-tuning or customizing foundation models; knowledge bases and vector stores (Amazon OpenSearch, Aurora pgvector, Amazon Kendra)
- Relevant AWS certifications (e.g., AWS Solutions Architect – Professional, Generative AI Developer – Professional)
- Experience supporting scientific research, federal government, healthcare, or similarly regulated environments
Benefits
- AI-powered career tool that identifies career steps and learning opportunities.
- An internal mobility team focused on helping you achieve your career goals.
- Full benefits.
- Wellness programs.
- 401K matching.
- Paid time off.
- Award-winning culture of innovation and a military-friendly workplace.
- Medical plan options, some with Health Savings Accounts.
- Dental plan options.
- A vision plan.
- A 401(k) plan offering the ability to contribute both pre- and post-tax dollars up to the IRS annual limits and receive a company match.
- Full flex work weeks where possible.
- A variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave.
- Typically 15 days of paid leave per calendar year for vacations, personal business, and illness, prorated based on the employee’s date of hire.
- An additional 10 paid holidays per year, prorated based on the employee’s date of hire.
- Up to 160 hours of paid leave in a rolling 12 month period through the GDIT Paid Family Leave program for eligible employees.
- Short- and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance are provided or available.
- Remote candidates will be considered; however, 2-3 days onsite in Rockville is strongly preferred.
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