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Swingtech

Government-focused IT, cybersecurity, and management services

AI/ML Engineer

AI Application EngineeringUpdated on Nov 13
Full-timeWashington, DC, USANo salary listed

About the Job

Requirements

  • A bachelor's degree in computer science, data science, software engineering, information systems, statistics, engineering, or a closely related technical field is required.
  • At least seven years of hands-on experience in AI/ML engineering, software engineering, data engineering, cloud engineering, or enterprise architecture is required.
  • At least two years of hands-on experience delivering generative AI, LLM integration, retrieval-augmented generation, model evaluation, agentic AI, production machine-learning systems, or comparable AI-enabled capabilities is required.
  • Demonstrated experience architecting and delivering secure enterprise or Federal AI solutions is required.
  • Experience with AI model integration, APIs, data pipelines, vector databases, retrieval systems, AI orchestration, continuous integration and continuous delivery, source control, model evaluation, monitoring, and MLOps is required.
  • Knowledge of FISMA, NIST 800-series guidance, FedRAMP, FIPS, security engineering, privacy, Section 508/WCAG accessibility, and Federal ATO or equivalent authorization processes is required.
  • Ability to advise technical and nontechnical stakeholders and lead work across AI, data, applications, UX, security, and program-management disciplines is required.
  • Must be willing to work three days onsite weekly at the customer site in Washington, DC.

Responsibilities

  • Lead AI solution architecture, design, engineering, integration, testing, deployment, troubleshooting, and technical quality for assigned DOL agency solutions.
  • Translate agency mission needs into actionable AI use cases, prototypes, technical designs, implementation backlogs, measurable acceptance criteria, and production-ready capabilities.
  • Design and implement AI/ML systems using appropriate approaches, including deterministic automation, classical machine learning, natural language processing, document intelligence, generative AI, large language models, retrieval-augmented generation, agentic workflows, multi-agent systems, and Model Context Protocol-based integrations.
  • Define and maintain reusable architecture patterns, engineering standards, evaluation methods, secure integration patterns, and MLOps/LLMOps practices across DOL agency teams.
  • Lead technical discovery and feasibility assessments, including data readiness, operational context, integration constraints, privacy and security impact, Responsible AI implications, and expected mission value.
  • Architect secure and scalable AI solutions using Government-approved cloud platforms, services, models, tools, data sources, APIs, repositories, and CI/CD pipelines.
  • Lead AI evaluation and TEVV activities addressing accuracy, relevance, retrieval quality, groundedness, hallucination, safety, reliability, bias and fairness, explainability, accessibility, performance, resiliency, and adversarial threats.
  • Ensure training, validation, and final evaluation datasets remain separated, documented, versioned, protected, and access-controlled.
  • Implement or oversee model versioning, experiment tracking, source control, automated testing, model and retrieval monitoring, drift detection, controlled retraining, rollback, and release-readiness controls.
  • Support Responsible AI documentation, AI risk assessments, RAIA packages, model cards, human-in-the-loop controls, AI use-case inventory inputs, and required Government approval packages.
  • Support security, privacy, Section 508 accessibility, ATO, architecture review, and operational-readiness activities.
  • Maintain source code, configurations, technical documents, testing evidence, runbooks, and release records in Government-controlled repositories.
  • Serve as a primary technical liaison to DOL agency stakeholders, the COR, Federal Project Manager, AI Governance, enterprise platform, cloud, security, privacy, architecture, and accessibility teams.
  • Provide peer review, technical coaching, quality oversight, and escalation support to the delivery team.
  • Support incident response, root-cause analysis, recovery, and corrective-action activities for production AI systems.

Desired Qualifications

  • A master's degree is preferred.
  • Experience delivering AI solutions for Federal civilian agencies, especially in regulated, privacy-sensitive, or high-impact environments, is preferred.
  • Experience with AWS, Azure AI Foundry, Google Cloud Vertex AI, AWS Bedrock, GitLab, GitHub Copilot, JIRA, Confluence, MLflow, containers, Kubernetes, and Infrastructure as Code is preferred.
  • Experience with AI red teaming, OWASP LLM security risks, AI risk management, model cards, Responsible AI governance, and formal AI evaluation frameworks is preferred.
  • Microsoft Azure AI, AWS AI/ML, Google Cloud AI/ML, Databricks, Snowflake, NVIDIA, CAIP, or equivalent AI/cloud certification is preferred.

About the Company

Swingtech

Government-focused IT, cybersecurity, and management services

Swingtech provides management and technology services to government and commercial clients, with a focus on the public sector. Its offerings include program management, IT services, cybersecurity, and financial consulting, and it earns revenue by securing contracts, especially with government agencies. The company uses the SBA 8(a) Business Development Program to win sole-source government contracts up to $4 million, helping it access certain opportunities. Its distinguishing factors are that it is woman-owned, leverages the 8(a) program, and combines a broad mix of services for a public-sector audience, aiming to deliver end-to-end improvements for clients.

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