Senior AI Engineer (AWS)

Type of Requisition:

Regular

Clearance Level Must Currently Possess:

None

Clearance Level Must Be Able to Obtain:

None

Public Trust/Other Required:

NACLC (T3)

Job Family:

Data Science and Data Engineering

Job Qualifications:

Skills:

AI Agents, AI Prompting, Amazon Bedrock, AWS Bedrock AgentCore, Generative AI

Certifications:

None

Experience:

8 + years of related experience

US Citizenship Required:

No

Job Description:

GDIT is looking for a Senior AI Engineer (AWS) to join our NIAID team, designing, building, and deploying AI solutions on AWS that serve the NIAID research community.

We are seeking a highly experienced and customer-focused engineer to architect, build, and evolve secure, scalable, and reliable AWS AI solutions supporting generative AI and scientific research. Our ideal candidate combines hands-on expertise across the AWS AI stack (Amazon Bedrock, Bedrock AgentCore, Amazon SageMaker, Amazon Q) with a strong command of modern application architecture, AI/LLM technologies, infrastructure, networking, identity, security, automation, and DevOps practices.

As a senior member of our Cloud Platform & DevOps team, you will serve as an AI engineering expert. You will work closely with application developers, AI engineers, cloud engineers, platform developers, security teams, customers, and other stakeholders to translate requirements into well-designed solutions.

This role is fully remote!

This role requires you to obtain and maintain a Public Trust and to provide onsite fingerprinting at a designated facility. This investigation may review personal and criminal behavior, financial conduct, foreign influence, as well as other adjudications.

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.

Required Qualifications:

• 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.

Preferred Qualifications:

• 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.
  

The likely salary range for this position is $129,813 - $166,750. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Scheduled Weekly Hours:

40

Travel Required:

None

Telecommuting Options:

Hybrid

Work Location:

Any Location / Remote

Total Rewards at GDIT:

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and 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. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. GDIT typically provides new employees with 15 days of paid leave per calendar year to be used for vacations, personal business, and illness and an additional 10 paid holidays per year. Paid leave and paid holidays are prorated based on the employee’s date of hire. The GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees. To ensure our employees are able to protect their income, other offerings such as 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. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

 

Our Identity Verification Process:

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.