AI/ML Engineer

General Dynamics IT; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

General Dynamics IT is seeking an AI/ML Engineer SME to drive advanced analytics within the Case Management Modernization program. The role delivers AI/ML capabilities, predictive models, and data-driven decision support for federal-grade applications.

The engineer will influence architecture, tooling, and governance while collaborating with cross-functional teams. The position emphasizes responsible AI, security, and compliance, with visibility into AI governance artifacts and lifecycle

Qualifications

• Education: BA/BS or equivalent required; MA/MS strongly preferred.
• Experience: 15+ years in information systems with at least 10+ years in specialized roles.

Responsibilities

• Define and execute AI/ML strategy aligned to CMM modernization objectives.
• Design, develop, deploy, and maintain ML, forecasting, Generative AI and AI analytics.
• Build and tune models with appropriate algorithms and data pipelines.
• Develop LLM-powered apps, RAG pipelines, AI agents, and automation capabilities.
• Ensure responsible AI, governance, security, and regulatory compliance.

Skills

Actionable Insights

Data Analysis

Data Analytics

Education

BA/BS or equivalent

MA/MS strongly preferred

Job description

Type of Requisition: Regular

Clearance Level Must Currently Possess: None

Clearance Level Must Be Able to Obtain: None

Public Trust/Other Required: BI Full 6C (T4)

Job Family: Data Science and Data Engineering

Job Qualifications

Skills: Actionable Insights, Data Analysis, Data Analytics Certifications: None Experience: 10 + years of related experience US Citizenship Required: No

Job Description

AI/ML ENGINEER SME

Own your opportunity to turn data into measurable outcomes for our customers' most complex challenges. As an AI/ML Engineer SME at GDIT, you'll power innovation to drive mission impact and grow your expertise to power your career forward.

MEANINGFUL WORK AND PERSONAL IMPACT

Seize your opportunity to make a personal impact supporting the Case Management Modernization (CMM) Program.

GDIT is your place to make meaningful contributions to challenging projects and grow a rewarding career. The AI/ML Engineer will be part of the CMM Data Modernization and Governance team responsible for delivering an integrated data governance, engineering, data platform, reporting, analytics, and Artificial Intelligence (AI)/Machine Learning (ML) capabilities that support operational decision-making and fulfill AO's data and analytics objectives in support of the CMM program.

The successful candidate will be responsible for delivering advanced analytics, visualizations, statistical modeling, and AI/ML capabilities; including Generative AI and Agentic AI solutions, predictive models, forecasting, and advanced analytics; that provide data-driven decision-support tools and actionable insights to users and stakeholders of the CMM application. This role provides technical leadership, strategic guidance, and tool recommendations to accelerate product development, and improve decision automation and overall CMM products. The role also oversees design, development, integration, and continuous enhancement advanced analytics and AI/ML capabilities in alignment with strict federal compliance requirements.

The AI/ML ENGINEER WILL EXECUTE THE FOLLOWING RESPONSIBILITIES

AI/ML & Advanced Analytics

• 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.

MLOps / LLMOps / AI Operations

• 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.

Responsible AI & AI Governance

• 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.

Collaboration & Innovation

• 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.

QUALIFICATIONS

• Education: BA/BS or equivalent required ; MA/MS strongly preferred.
• Experience: 15+ years of general experience in information systems with at least 10+ of those years involving specialized experience requir