Swingtech

Data Engineer

• Design, build, test, deploy, and maintain scalable data pipelines for batch, streaming, near-real-time, and event-driven workloads
• Integrate approved agency data sources, APIs, file stores, document repositories, relational databases, data lakes, data warehouses, and authorized external sources
• Develop ETL/ELT pipelines for data extraction, validation, transformation, normalization, enrichment, de-identification, metadata management, and loading
• Implement document-ingestion pipelines supporting OCR, parsing, classification, metadata extraction, PII detection/redaction, chunking, embeddings, vector indexing, and retrieval workflows
• Create and maintain data models, schemas, data dictionaries, metadata structures, catalog records, and data-quality controls
• Implement data lineage, source provenance, dataset versioning, retention, access controls, and auditability for training, validation, evaluation, and production datasets
• Preserve separation of training, validation, and final evaluation datasets through controlled access, versioning, and documented lifecycle processes
• Develop and monitor data-quality measures including completeness, accuracy, timeliness, duplication, validity, freshness, distribution drift, and labeling quality
• Apply data minimization, masking, encryption, access controls, de-identification, and least-privilege safeguards to PII, CUI, and other protected DOL data
• Collaborate with AI/ML Engineers to optimize retrieval quality, embeddings, vector stores, hybrid search, reranking, citation traceability, and knowledge-base refresh processes
• Develop data-pipeline runbooks, technical documentation, source inventories, lineage artifacts, data-quality reports, and operational support procedures
• Support security, privacy, ATO, Responsible AI, incident response, MLOps, monitoring, and release-readiness activities

AI/ML Data Engineer – Hybrid, US Citizens/Green Cards

AI Engineer

• Develop full-stack AI-enabled applications, APIs, microservices, dashboards, workflow automations, and enterprise-system integrations
• Implement capabilities using approved LLMs, RAG pipelines, classification models, document intelligence, predictive analytics, generative AI, agentic workflows, and MCP-based services
• Develop backend services integrating approved models, vector stores, data platforms, identity providers, enterprise systems, and Government-approved cloud services
• Build accessible web interfaces and dashboards meeting Section 508 and WCAG 2.1 Level A/AA requirements
• Implement human-in-the-loop controls, including review queues, decision-support displays, overrides, approvals, escalations, correction/feedback workflows, audit trails, and role-based access
• Ensure AI outputs are clearly identified, grounded in approved sources, and presented with citations, limitations, and required user controls
• Develop modular, maintainable, testable code using secure software-development practices, code reviews, version control, automated testing, and CI/CD
• Implement application-security controls including authentication, authorization, input validation, API security, secrets management, encryption, logging, error handling, and rate limiting
• Support AI-security controls including prompt-injection defenses, safe prompt/context handling, output validation, controlled tool use, and audit logging
• Develop and maintain unit, integration, API, regression, performance, security, and accessibility tests
• Create and maintain technical documentation, architecture records, configuration documentation, deployment scripts, runbooks, release notes, and knowledge-transfer artifacts
• Support production monitoring, release activities, incident response, defect resolution, and continuous improvement
• Support DOL agency missions as part of Swingtech’s federal and intelligence-community IT services

AI Developer – Local to DMV

Security Engineer

• Design, assess, document, and improve cybersecurity, privacy, and AI-specific security controls for DOL AI systems
• Develop and implement AI security architecture, threat models, control matrices, security requirements, abuse cases, test plans, and remediation plans
• Implement and validate security controls across AI applications, LLM integrations, data pipelines, model endpoints, RAG systems, vector stores, MCP servers, APIs, orchestration services, and CI/CD pipelines
• Conduct AI-specific security testing, including prompt injection, jailbreaks, malicious-input attacks, retrieval manipulation, data poisoning, model extraction, model inversion, credential compromise, access-control bypass, insecure output handling, and tool-abuse scenarios
• Apply Zero Trust, least privilege, role-based access, FIPS-validated encryption, secrets management, audit logging, secure configuration, vulnerability management, and secure software-development practices
• Support FISMA, RMF, and ATO activities, including security categorization, system boundaries, SSPs, SAPs, SARs, POA&Ms, continuous monitoring, security assessments, risk decisions, and remediation evidence
• Support assessment and approval of AI models, third-party AI services, cloud services, model providers, APIs, tools, and data-handling practices before integration into DOL systems
• Validate that approved cloud AI services satisfy applicable FedRAMP requirements and DOL authorization expectations
• Ensure PII, CUI, prompts, retrieval context, embeddings, model outputs, logs, backups, and evaluation data are protected through approved controls
• Support AI Incident Response Plan development and maintenance, including escalation paths, evidence preservation, reporting templates, severity classification, containment procedures, and post-incident review
• Coordinate security incident investigation, containment, mitigation, recovery, and reporting for suspected or confirmed security events
• Support supply-chain security, SBOM generation, dependency scanning, secure-development attestations, vulnerability remediation, and third-party risk management
• Collaborate with engineering teams to integrate security into development, testing, deployment, and production operations

AI Security Engineer – US Citizens/Green Cards

Machine Learning Engineer

• Serve as a senior Forward Deployed Engineer and accountable technical lead for one or more DOL component agencies
• Lead AI solution architecture, design, engineering, integration, testing, deployment, troubleshooting, and technical quality for assigned DOL agency solutions
• Translate agency mission needs into AI use cases, prototypes, technical designs, implementation backlogs, acceptance criteria, and production-ready capabilities
• Design and implement AI/ML systems using deterministic automation, classical ML, NLP, document intelligence, generative AI, LLMs, RAG, agentic workflows, multi-agent systems, and MCP-based integrations
• Define reusable architecture patterns, engineering standards, evaluation methods, secure integration patterns, and MLOps/LLMOps practices
• Lead technical discovery and feasibility assessments covering data readiness, operational context, integration constraints, privacy/security impact, Responsible AI implications, and 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 are 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 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 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

Senior AI/ML Engineer – US Citizens/Green Cards only

• Develop AI/ML-enabled applications, APIs, data-processing components, model integration layers, RAG pipelines, retrieval services, workflow automations, and technical prototypes
• Support model development, fine-tuning, prompt/context engineering, evaluation, version control, release management, and production monitoring
• Build RAG capabilities using document ingestion, parsing, metadata extraction, chunking, embeddings, vector indexing, hybrid retrieval, reranking, citation validation, and knowledge-base refresh processes
• Implement agentic and workflow automation features, including MCP server or tool integrations, schema validation, controlled tool calls, audit logging, human-approval checkpoints, and safe failure handling
• Develop robust code in Python, SQL, and other required languages using secure software-development practices
• Create automated unit, integration, regression, data-quality, model-evaluation, and performance tests
• Support AI evaluation for accuracy, relevance, hallucination, grounding, bias/fairness, explainability, safety, security, and user acceptance
• Participate in CI/CD, DevSecOps, MLOps, code review, security scanning, documentation, and source-control processes
• Prepare technical documentation, runbooks, test evidence, release notes, model documentation, and configuration records
• Support privacy, security, Responsible AI, accessibility, and ATO evidence-development activities
• Support operational monitoring, incident response, defect triage, corrective actions, and knowledge transfer
• Participate in agile ceremonies, demonstrations, backlog refinement, sprint planning, and retrospective improvement activities
• Collaborate with Senior AI/ML Engineers, data engineers, developers, business analysts, project managers, and DOL stakeholders to deliver secure, measurable, and maintainable AI capabilities

AI/ML Data Engineer – Hybrid, US Citizens/Green Cards

AI Developer – Local to DMV

AI Security Engineer – US Citizens/Green Cards

Senior AI/ML Engineer – US Citizens/Green Cards only

AI/ML Engineer, Mid-Level