aimlroles

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

Swingtech Open · verified Oct 22, 2026
Washington Full-time Mid-level AI Engineering

At a glance

Mid-level AI Engineering role at Swingtech. Washington · full-time · no salary stated · we estimate $138,900–$261,750.

Estimated pay

Swingtech has not published a salary for this role. The figure below is our estimate, not theirs.

$138,900 – $261,750
What the middle half of mid-level AI engineering roles in Washington paid, among postings that did state a salary.
Worked out from 12 postings that stated pay, median $162,000. Last updated Oct 21, 2026.
RoleAI Engineering
SeniorityMid-level
LocationWashington
EmploymentFull-time
PostedSep 23, 2026 · 4w ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build and operate data pipelines for batch, streaming, near-real-time and event-driven workloads
  • Connect approved agency sources, then transform and load data with validation, enrichment and de-identification
  • Prepare documents for search by handling OCR, parsing, PII protection, embeddings and vector indexing
  • Keep data models, metadata, quality checks, lineage and dataset versions usable across AI/ML workflows
  • Work with AI/ML engineers on retrieval quality, search, reranking, citation tracking and knowledge-base updates

What you bring

  • A bachelor's degree in a technical discipline such as computer science, data engineering or a related field
  • At least four years in data engineering, database development, ETL/ELT or another listed area
  • Strong SQL and Python skills, plus experience building pipelines and connecting data sources
  • Hands-on work with data modeling, quality, lineage, transformation, monitoring and operational support
  • Knowledge of cloud data services and secure handling practices, including access controls, encryption and PII protection

Who this fits

This role suits a mid-career data engineer who can support secure data workflows for analytics and AI/ML applications. You must be a U.S. citizen or green card holder and local to the DMV. The job requires three onsite days each week at the customer site in Washington, DC.

From the employer

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 AI/ML Data Engineer develops and sustains the secure data pipelines, data products, retrieval foundations, and governance controls that enable DOL’s AI/ML solutions. The position supports structured, semi-structured, and unstructured data sources used for analytics, AI/ML development, document intelligence, RAG, and production AI applications.

Essential Duties

  • 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 that support 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 the 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.

Required Qualifications

  • Bachelor’s degree in computer science, data engineering, data science, information systems, software engineering, mathematics, or a related technical discipline.
  • At least four years of experience in data engineering, database development, analytics engineering, ETL/ELT development, data-platform implementation, or related work.
  • Strong SQL and Python development skills.
  • Experience designing data pipelines and integrating APIs, databases, file systems, cloud storage, data warehouses, or data lakes.
  • Experience with data modeling, metadata, data quality, data lineage, data transformation, monitoring, and operational support.
  • Familiarity with AWS, Azure, Google Cloud, or equivalent cloud data services.
  • Knowledge of secure data-handling practices, including access control, encryption, data masking, PII protection, and logging.
  • Must be willing to work 3 days onsite at customer site in Washington, DC.

Preferred Qualifications

  • Experience with AWS Glue, S3, Athena, Redshift, Lake Formation, Azure Data Factory, Azure Data Lake Storage, Databricks, Snowflake, BigQuery, or equivalent platforms.
  • Experience with vector databases or vector-search capabilities, including OpenSearch, pgvector, Pinecone, Weaviate, Milvus, Chroma, FAISS, or similar tools.
  • Experience with RAG, document intelligence, OCR, enterprise search, knowledge management, document classification, or content-ingestion pipelines.
  • Familiarity with Federal data governance, FedRAMP, FISMA, NIST 800-53, NIST 800-171, CUI, Privacy Act, and records-management requirements.

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