AI Engineer
Skills
About the role
Clearance Level
Other
Category
Data Science and Data Engineering
Location
Sterling, the USA
(Onsite Workplace)
Key Skills For Success
Artificial Intelligence (AI)
Machine Learning (ML)
Natural Language Processing (NLP)
REQ#: RQ226699
Public Trust: None
Requisition Type: Regular
Your Impact
Own your opportunity to work alongside federal civilian agencies. Make an impact by providing services that help the government ensure the well being and support of U.S. citizens.
Job Description
Job Description:
As an AI/ML Engineer Associate, the work you’ll do at GDIT will be impactful to the mission of the Diplomatic Security Bureau of the Department of State. You will play a crucial role as part of a team to develop, implement and maintain an AI powered solution leveraging existing Department of State data and reports that will deliver insights and assist in decision making for Diplomatic Security Leaders and Analysts.
Core responsibilities:
RAG Pipeline Development & Maintenance
Implement and iterate document ingestion, chunking, and embedding pipelines (e.g., Nomic Embed v1.5)
Tune retrieval parameters (chunk size, overlap, top-k, similarity thresholds) against evaluation sets
Maintain and troubleshoot the vector store (PGVector on PostgreSQL) - indexing, query performance, schema updates
Model Serving & Inference Support
Support day-to-day operation of the LLM serving layer
Assist with model updates, version testing, and rollback procedures
Monitor GPU utilization, memory usage, and inference latency
Application Integration
Work within front-end integrations to wire up new features, prompt templates, or tool-calling workflows
Build and maintain API integrations between the LLM layer and downstream applications (via PGBouncer/Postgres, Redis caching, etc.)
Write and refine system prompts, few-shot examples, and prompt-engineering iterations for specific use cases
Evaluation & Quality
Build/run evaluation harnesses to test retrieval accuracy and generation quality (hallucination checks, relevance scoring)
Track regressions when models, embeddings, or chunking strategies change
Document known failure modes and edge cases
Infrastructure support (Junior level)
Assist with environment setup, dependency management, and container/service configuration in development environments
Support basic troubleshooting of Redis, PostgreSQL, PGAdmin as they relate to the RAG pipeline
Escalate deeper infra/networking issues to senior engineers or platform team
Test Strategy & Planning
Contribute to a test strategy for the RAG/LLM pipeline covering three distinct layers: retrieval quality (are the right chunks being pulled), generation quality (is the LLM producing accurate, grounded, non-hallucinated answers), and system/integration (does the pipeline work end-to-end under real conditions)
Help define acceptance criteria for "good enough" retrieval and generation - e.g., minimum relevance score thresholds, acceptable hallucination rate, latency SLAs
Participate in test planning for new features or model/embedding swaps - identify what could break (retrieval drift, prompt regressions, latency changes) before rollout
Maintain a golden/reference dataset of representative queries and expected answers or expected retrieved sources, used as a stable benchmark across changes
Test Execution
Execute manual exploratory testing for new features or edge cases automation doesn't yet cover - adversarial prompts, out-of-scope questions, ambiguous queries, multi-turn context handling
Run pre-deployment validation checklists before pushing model, prompt, or pipeline changes to production
Execute periodic regression passes on a schedule (not just at release time) to catch silent drift - since RAG/LLM systems can degrade without any code change (e.g., underlying model provider updates, data staleness)
Validate fixes against the original defect/failure case plus the broader regression suite
Defect management
Documentation & knowledge transfer
Maintain technical documentation for pipelines, configs, and architecture decisions
Document runbooks for common operational tasks (restarting services, common errors, model swap procedures)
Collaboration
Collaborate with senior engineers on architecture decisions
Participate in code review, both giving and receiving feedback
Communicate technical constraints/tradeoffs to non-technical stakeholders as required
Technical Skills: Python, Machine Learning, Deep Learning, SQL, Data Science, PyTorch, Docker, TensorFlow, Artificial Intelligence, Natural Language Processing, Linux, JavaScript, MATLAB, Architecture, Data Analytics, Kubernetes, MSFT Azure Platform, Big Data, Hadoop, Visualization, Software Development, and Agile.
Work Requirements
Years of Experience
0 + years of related experience
may vary based on technical training, certification(s), or degree
Certification
Travel Required
Less than 10%
Salary and Benefit Information
The likely salary range for this position is $55,462 - $75,038. 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.
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.
About Our Work
We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.
Join our Talent Community to stay up to date on our career opportunities and events at gdit.com/tc.
Compensation
This Machine Learning Engineer role pays $55k-$75k/yr. Within typical range for machine learning engineer roles in United States.
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