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AI/ML Engineer (Senior)-Hybrid (US Citizens/ Green Cards- Local to DMV only)

Washington, DC

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Apply at Swingtech-Careers

What you’ll work on

Full posting

The Senior AI/ML Engineer serves as a senior Forward Deployed Engineer and accountable technical lead for one or more DOL component agencies.

Senior AI/ML Engineer positions serve as the program’s shared technical leadership team and maintain designated agency technical points of contact.

  • Lead AI solution architecture, design, engineering, integration, testing, deployment, troubleshooting, and technical quality for assigned DOL agency solutions.

  • Define and maintain reusable architecture patterns, engineering standards, evaluation methods, secure integration patterns, and MLOps/LLMOps practices across DOL agency teams.

  • Ensure training, validation, and final evaluation datasets remain separated, documented, versioned, protected, and access-controlled.

From the employer’s posting
The Senior AI/ML Engineer serves as a senior Forward Deployed Engineer and accountable technical lead for one or more DOL component agencies. The position provides hands-on technical leadership across AI solution architecture, data engineering, AI/ML development, generative AI, RAG, agentic workflows, Model Context Protocol integrations, evaluation, MLOps, production deployment, and ongoing operations.
Senior AI/ML Engineer positions serve as the program’s shared technical leadership team and maintain designated agency technical points of contact.
Essential Duties 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 ML, NLP, document intelligence, generative AI, LLMs, RAG, agentic workflows, multi-agent systems, and MCP-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/security impact, Responsible AI implications, and expected mission value.
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.

What you’ll bring

All qualifications

Core experience

  • Demonstrated experience architecting and delivering secure enterprise or Federal AI solutions.
  • Experience with AI model integration, APIs, data pipelines, vector databases, retrieval systems, AI orchestration, CI/CD, source control, model evaluation, monitoring, and MLOps.
  • Demonstrated knowledge of FISMA, NIST 800-series guidance, FedRAMP, FIPS, security engineering, privacy, Section 508/WCAG accessibility, and Federal ATO or equivalent authorization processes.
  • Ability to advise both technical and nontechnical stakeholders and lead work across AI, data, applications, UX, security, and program-management disciplines.

Preferred experience

  • Bachelor’s degree in computer science, data science, software engineering, information systems, statistics, engineering, or a closely related technical field; master’s degree preferred.
  • Experience delivering AI solutions for Federal civilian agencies, especially in regulated, privacy-sensitive, or high-impact environments.
  • Experience with AWS, Azure AI Foundry, Google Cloud Vertex AI, AWS Bedrock, GitLab, GitHub Copilot, JIRA, Confluence, MLflow, containers, Kubernetes, and Infrastructure as Code.
  • Experience with AI red teaming, OWASP LLM security risks, AI risk management, model cards, Responsible AI governance, and formal AI evaluation frameworks.
Qualification wording
Demonstrated experience architecting and delivering secure enterprise or Federal AI solutions.
Experience with AI model integration, APIs, data pipelines, vector databases, retrieval systems, AI orchestration, CI/CD, source control, model evaluation, monitoring, and MLOps.
Demonstrated knowledge of FISMA, NIST 800-series guidance, FedRAMP, FIPS, security engineering, privacy, Section 508/WCAG accessibility, and Federal ATO or equivalent authorization processes.
Ability to advise both technical and nontechnical stakeholders and lead work across AI, data, applications, UX, security, and program-management disciplines.
Bachelor’s degree in computer science, data science, software engineering, information systems, statistics, engineering, or a closely related technical field; master’s degree preferred.
Experience delivering AI solutions for Federal civilian agencies, especially in regulated, privacy-sensitive, or high-impact environments.
Experience with AWS, Azure AI Foundry, Google Cloud Vertex AI, AWS Bedrock, GitLab, GitHub Copilot, JIRA, Confluence, MLflow, containers, Kubernetes, and Infrastructure as Code.
Experience with AI red teaming, OWASP LLM security risks, AI risk management, model cards, Responsible AI governance, and formal AI evaluation frameworks.
Education & alternatives
Required Qualifications - Bachelor’s degree in computer science, data science, software engineering, information systems, statistics, engineering, or a closely related technical field; master’s degree preferred. - At least seven years of hands-on experience in AI/ML engineering, software engineering, data engineering, cloud engineering, or enterprise architecture.

Tools in this posting

  • AWS
  • Azure
  • Databricks
  • Kubernetes
  • MLflow
  • Snowflake
  • Google Cloud (GCP)
Source — Tool mentions in context
- Experience delivering AI solutions for Federal civilian agencies, especially in regulated, privacy-sensitive, or high-impact environments. - Experience with AWS, Azure AI Foundry, Google Cloud Vertex AI, AWS Bedrock, GitLab, GitHub Copilot, JIRA, Confluence, MLflow, containers, Kubernetes, and Infrastructure as Code. - Experience with AI red teaming, OWASP LLM security risks, AI risk management, model cards, Responsible AI governance, and formal AI evaluation frameworks.
- Experience with AI red teaming, OWASP LLM security risks, AI risk management, model cards, Responsible AI governance, and formal AI evaluation frameworks. - Microsoft Azure AI, AWS AI/ML, Google Cloud AI/ML, Databricks, Snowflake, NVIDIA, CAIP, or equivalent AI/cloud certification. Summary of Benefits

About Swingtech-Careers

Swingtech delivers innovative Information Technology and Professional Support services to a diverse range of clients across the federal and intelligence communities.

In the employer’s words · Read in context

Job description

View original posting ↗

About Swingtech

Swingtech delivers innovative Information Technology and Professional Support services to a diverse range of clients across the federal and intelligence communities. With over 15 years of trusted experience as a systems integrator, we apply agile methodologies and deep industry insight to help our customers achieve greater efficiency, compliance, and cost savings. At Swingtech, we’re committed to excellence and long-term success for our clients and our team.

Position Summary

The Senior AI/ML Engineer serves as a senior Forward Deployed Engineer and accountable technical lead for one or more DOL component agencies. The position provides hands-on technical leadership across AI solution architecture, data engineering, AI/ML development, generative AI, RAG, agentic workflows, Model Context Protocol integrations, evaluation, MLOps, production deployment, and ongoing operations.


Senior AI/ML Engineer positions serve as the program’s shared technical leadership team and maintain designated agency technical points of contact.

Essential Duties

  • 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 ML, NLP, document intelligence, generative AI, LLMs, RAG, agentic workflows, multi-agent systems, and MCP-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/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.

Required Qualifications

  • Bachelor’s degree in computer science, data science, software engineering, information systems, statistics, engineering, or a closely related technical field; master’s degree preferred.
  • At least seven years of hands-on experience in AI/ML engineering, software engineering, data engineering, cloud engineering, or enterprise architecture.
  • At least two years of hands-on experience delivering generative AI, LLM integration, RAG, model evaluation, agentic AI, production ML systems, or comparable AI-enabled capabilities.
  • Demonstrated experience architecting and delivering secure enterprise or Federal AI solutions.
  • Experience with AI model integration, APIs, data pipelines, vector databases, retrieval systems, AI orchestration, CI/CD, source control, model evaluation, monitoring, and MLOps.
  • Demonstrated knowledge of FISMA, NIST 800-series guidance, FedRAMP, FIPS, security engineering, privacy, Section 508/WCAG accessibility, and Federal ATO or equivalent authorization processes.
  • Ability to advise both technical and nontechnical stakeholders and lead work across AI, data, applications, UX, security, and program-management disciplines.
  • Must be willing to work 3 days onsite at customer site in Washington, DC.

Preferred Qualifications

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

Summary of Benefits

  • 15 PTO days
  • 11 paid holidays
  • Medical Insurance with – 3 options (HSA with $600 Employer Contribution).
  • Dental Insurance with no age limit orthodonture.
  • Vision Insurance through EyeMed in and out of network coverage.
  • Short Term and Long-Term Disability coverage with 100% premium support,
  • Life insurance and AD&D with 100% premium support
  • Supplemental Life Insurance
  • Critical Care and Accident Insurance availability
  • Pet Insurance through Nationwide
  • Employee Assistance Program
  • 401k with enrollment from day one. 4% deferral by company.
  • $1500 Annual Training Budget
  • $1500 Referral bonus
  • Eligibility for annual merit and discretionary bonus
  • Flexible work arrangements

Equal Opportunity Employer Minority/Female/Veterans/Disabled

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

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Location & working pattern

Washington, DC

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Status in our records
Active
First seen by us
Sep 22, 2026
Recorded sightings
9
Last seen by us
Oct 7, 2026
Employer says posted
Sep 18, 2026

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