AI/ML Engineer

LED FastStart•Louisiana, MO

3d•$195,240 - $264,148•Remote

About The Position

GDIT is seeking an AI/ML Engineer SME to join the Case Management Modernization (CMM) Program's Data Modernization and Governance team. This role will be responsible for delivering integrated data governance, engineering, data platform, reporting, analytics, and AI/ML capabilities to support operational decision-making and achieve data and analytics objectives for the CMM program. The successful candidate will provide advanced analytics, visualizations, statistical modeling, and AI/ML capabilities, including Generative AI and Agentic AI solutions, predictive models, forecasting, and advanced analytics. This role offers technical leadership, strategic guidance, and tool recommendations to accelerate product development and improve decision automation. The position also oversees the design, development, integration, and continuous enhancement of advanced analytics and AI/ML capabilities in compliance with federal regulations.

Requirements

BA/BS or equivalent required; MA/MS strongly preferred.
15+ years of general experience in information systems with at least 10+ of those years involving specialized experience required.
Expertise in machine learning, deep learning, and natural language processing (NLP) techniques.
Experience in AI/ML engineering, machine learning, data science, or advanced analytics.
Strong proficiency with Python, SQL, ML/DL frameworks (TensorFlow, PyTorch, scikit-learn, XGBoost) and cloud AI services (AWS SageMaker, Bedrock, Azure ML, GCP Vertex AI).
Experience implementing MLOps pipelines and integrating ML workflows into CI/CD environments.
Knowledge of federal compliance frameworks such as FedRAMP, FISMA, and NIST AI RMF.
Understanding data governance, model monitoring, and ethical AI practices.
Strong analytical, advisory, and communication skills to bridge strategy, engineering, and business outcomes.
Experience with vector databases, LLM fine-tuning, and Retrieval-Augmented Generation (RAG) pipelines, prompt engineering, and/or Agentic AI architectures.
Experience with MLOps/LLMOps (MLflow, SageMaker, Vertex AI, or Azure ML), model deployment, versioning, monitoring, and lifecycle management.
Experience with Generative AI/LLM frameworks (LangChain, vector databases, OpenAI/Azure).
Excellent presentation and communication skills.
Consultant mindset with the ability to work with high level customer stakeholders and build excellent customer relationships.
Experience identifying and applying industry tools, solutions, methods best practices, and emerging technologies.
Strong analytical skills and problem-solving skills with the ability to formulate and communicate recommendations for improvement.
Demonstrated ability to work effectively, independently, and as part of a team.
Must be a US Person (Green Card Holder, US Permanent Resident Alien, Refugee, Asylee, or US Citizen).
Must be able to pass a background check to obtain a position of Public Trust.

Nice To Haves

Experience leading federal or judiciary AI/ML modernization programs.
Familiarity with Generative AI for content generation, summarization, and development assistance.
Experience applying predictive analytics to performance monitoring, test optimization, and resource planning.
Background in data visualization and explainable AI (XAI) methods.
Data Visualization and Data Story Telling certifications
Tableau Certified Data Analyst, Tableau Desktop Specialist
Power BI Data Analyst
Story Telling with Data
Certified Data Management Professional (CDMP)
Snowflake SnowPro Core
Databricks Certified Data Professional
AWS Certified Data Analytics - Specialty
AWS Certified Solutions Architect - Professional
AWS Certified Data Engineer
AWS Certified Machine Learning - Specialty or Google Professional ML Engineer
Certified AI Governance Professional (AIGP) or NIST AI RMF certification
SAFe Architect (ARCH) or SAFe DevOps Practitioner (SDP)
PMP or ITIL 4 Foundation

Responsibilities

Define and execute AI/ML strategy aligned to CMM modernization objectives.
Design, develop, deploy, and maintain ML, predictive, forecasting, Generative AI, Agentic AI, and advanced analytics solutions.
Build and tune models using appropriate algorithms, architectures, and data pipelines.
Develop LLM-powered applications, RAG pipelines, AI agents, and intelligent automation capabilities.
Apply statistical and advanced analytics methods to support data-driven decision-making.
Evaluate foundation models, commercial/open-source models, and emerging AI technologies.
Create proof-of-concepts and transition successful models to production.
Document AI/ML architecture, methodologies, features, and validation results.
Automate model deployment, monitoring, versioning, lineage, and lifecycle management.
Build and maintain MLOps/LLMOps pipelines integrated with CI/CD and DevSecOps.
Implement automated model training, testing, validation, deployment, rollback, and alerting.
Monitor model performance, drift, and degradation; trigger retraining as needed.
Maintain reproducible environments and support scalable cloud deployment.
Integrate AI/ML pipelines with data engineering and cloud platform services.
Ensure compliance with Responsible AI requirements: transparency, fairness, explainability, security, and privacy.
Perform bias assessments, model risk evaluations, and bias mitigation strategies.
Conduct and document explainability assessments and model interpretability.
Lead ATO impact analysis for AI/ML capabilities, support security, privacy, and authorization reviews.
Maintain the AI/ML Capability Register, model cards, governance artifacts, and lifecycle documentation.
Support AI/ML security assessments, privacy reviews, data classification assessments, and authorization activities.
Identify risks such as hallucination, prompt injection, data leakage, misuse, and drift; implement safeguards and monitoring.
Support federal AI, cybersecurity, privacy, and governance compliance.
Partner with analysts, engineers, architects, governance, cybersecurity, and business stakeholders.
Translate business problems into AI/ML use cases and technical solutions.
Assess data readiness and ensure appropriate data ownership, quality, and lineage.
Develop standards, reusable patterns, and best practices for AI/ML development.
Recommend AI/ML tools, cloud services, and SDLC automation opportunities.
Mentor teams on AI/ML development and Responsible AI practices.
Communicate technical findings clearly to both technical and non-technical audiences.

Benefits

Comprehensive benefits and wellness packages
401K with company match
Competitive pay
Paid time off
Variety of medical plan options
Health Savings Accounts
Dental plan options
Vision plan
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
Variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave.
15 days of paid leave per calendar year to be used for vacations, personal business, and illness
10 paid holidays per year
Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees.
Short and long-term disability benefits
Life insurance
Accidental death and dismemberment insurance
Personal accident insurance
Critical illness insurance
Business travel and accident insurance