AI Engineer Jobs in District of Columbia
AI Engineer jobs in District of Columbia concentrate heavily in federal government contracting, defense intelligence, and policy-driven technology sectors, with demand ranging from mid-level practitioners to senior architects and research leads. Most hiring is centered in Washington DC proper, with additional activity in the surrounding Virginia and Maryland corridors, where established contractors like Booz Allen Hamilton, Leidos, and SAIC maintain large AI and data science practices. Natural language processing, machine learning operations, and AI ethics and governance are among the most sought-after specialties given the region's regulatory and national security focus. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 58+ AI Engineer jobs
Full time
Hybrid model
Washington, DC
The Data Engineer in this role will support programs involving one or more of the following:
responsible for building persistent cloud data pipelines, integrating microservices, and structuring data to power Amazon OpenSearch, Amazon Neptune (Knowledge Graphs), and Amazon SageMaker for advanced analytics.
2. Scope of Work
2.1 Pipeline Development and Implementation
- Build continuous, event-driven streaming pipelines using Amazon EventBridge and SQS.
- Orchestrate complex ELT transformations using EKS and Databricks.
- Develop automated data feeds for the enterprise data platform and downstream applications.
- Design and populate graph data models for Amazon Neptune to support entity relationship tracking.
- Build and optimize vector indexes for Amazon OpenSearch to power the platform's AI/ML and RAG Q&A capabilities.
- Ensure real-time or near-real-time data latency targets are met for operational dashboards.
- Partner directly with AI/ML Data Scientists to ensure data is properly curated, partitioned, and served for real-time model inference.
- Support front-end developers by building reliable, performant data APIs.
- Present pipeline architectures during technical reviews.
- Implement fine-grained, row-level Access Control to secure sensitive procurement data.
- Set up Amazon CloudWatch and Dynatrace for continuous pipeline monitoring, alerting, and telemetry.
- Ensure data served to AI models is clean and unbiased according to institutional guidelines.
- Maintain architectural diagrams for streaming data flows.
- Write API endpoint documentation and AI data prep runbooks.
3.1 Education
- Bachelor’s or Master’s in Computer Science, Data Engineering, or a related quantitative field.
- AWS Certified Data Engineer – Associate or Microsoft Certified Azure Data Engineer. OR AWS ML Specialty
- 5+ years building continuous data pipelines, real-time streaming architectures, and preparing data for machine learning workflows.
- Expert SQL and Python.
- Deep expertise in AWS ecosystem (EKS, Lambda, SQS, OpenSearch, Neptune, Bedrock) and Apache Spark/Databricks.
- Strong architectural mindset, capability to handle hight-veolocity data, and enthusiasm for integrating foundational AI/ML services.
Application Accepted: 7/30/2026
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
Salary and Other Compensation:
The annual salary for this position is between $125,000 - $140,000 depending on experience and other qualifications of the successful candidate
Medical/Dental/Vision/Life Insurance
- Paid holidays plus Paid Time Off
- 401(k) plan and contributions
- Long-term/Short-term Disability
- Paid Parental Leave
- Employee Stock Purchase Plan
Our strength is built on our ability to work together. Our diverse backgrounds offer different perspectives and new ways of thinking. It encourages lively discussions, creativity, productivity, and helps us build better solutions for our clients. We want someone who thrives in this setting and is inspired to craft meaningful solutions through true collaboration.
If you are content with ambiguity, excited by change, and excel through autonomy, we’d love to hear from you!
#LI-AV1#CB#Ind123
Full time
Hybrid model
Washington, DC
The Data Engineer in this role will support programs involving one or more of the following:
responsible for building persistent cloud data pipelines, integrating microservices, and structuring data to power Amazon OpenSearch, Amazon Neptune (Knowledge Graphs), and Amazon SageMaker for advanced analytics.
2. Scope of Work
2.1 Pipeline Development and Implementation
- Build continuous, event-driven streaming pipelines using Amazon EventBridge and SQS.
- Orchestrate complex ELT transformations using EKS and Databricks.
- Develop automated data feeds for the enterprise data platform and downstream applications.
- Design and populate graph data models for Amazon Neptune to support entity relationship tracking.
- Build and optimize vector indexes for Amazon OpenSearch to power the platform's AI/ML and RAG Q&A capabilities.
- Ensure real-time or near-real-time data latency targets are met for operational dashboards.
- Partner directly with AI/ML Data Scientists to ensure data is properly curated, partitioned, and served for real-time model inference.
- Support front-end developers by building reliable, performant data APIs.
- Present pipeline architectures during technical reviews.
- Implement fine-grained, row-level Access Control to secure sensitive procurement data.
- Set up Amazon CloudWatch and Dynatrace for continuous pipeline monitoring, alerting, and telemetry.
- Ensure data served to AI models is clean and unbiased according to institutional guidelines.
- Maintain architectural diagrams for streaming data flows.
- Write API endpoint documentation and AI data prep runbooks.
3.1 Education
- Bachelor’s or Master’s in Computer Science, Data Engineering, or a related quantitative field.
- AWS Certified Data Engineer – Associate or Microsoft Certified Azure Data Engineer. OR AWS ML Specialty
- 5+ years building continuous data pipelines, real-time streaming architectures, and preparing data for machine learning workflows.
- Expert SQL and Python.
- Deep expertise in AWS ecosystem (EKS, Lambda, SQS, OpenSearch, Neptune, Bedrock) and Apache Spark/Databricks.
- Strong architectural mindset, capability to handle hight-veolocity data, and enthusiasm for integrating foundational AI/ML services.
Application Accepted: 7/30/2026
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
Salary and Other Compensation:
The annual salary for this position is between $125,000 - $140,000 depending on experience and other qualifications of the successful candidate
Medical/Dental/Vision/Life Insurance
- Paid holidays plus Paid Time Off
- 401(k) plan and contributions
- Long-term/Short-term Disability
- Paid Parental Leave
- Employee Stock Purchase Plan
Our strength is built on our ability to work together. Our diverse backgrounds offer different perspectives and new ways of thinking. It encourages lively discussions, creativity, productivity, and helps us build better solutions for our clients. We want someone who thrives in this setting and is inspired to craft meaningful solutions through true collaboration.
If you are content with ambiguity, excited by change, and excel through autonomy, we’d love to hear from you!
#LI-AV1#CB#Ind123
See All 58 AI Engineer Jobs in District of Columbia
Find roles in District of Columbia that match your experience and apply in just a few clicks.
Find AI Engineer JobsAI Engineer Jobs by City in District of Columbia
Where District of Columbia roles are concentrated, by current openings.
AI Engineer Job Market in District of Columbia
A snapshot from current District of Columbia openings, updated as new roles post.
Who's Hiring
- Booz Allen Hamilton11
- Humana3
- Comcast3
- The Carlyle3
- AARP2
Top Industries Hiring
- Consulting & Professional Services7
- Technology & Software6
- Healthcare & Medical Services4
- Agriculture & Farming3
- Investment & Asset Management3
What District of Columbia Employers Look For
The qualifications that appear most often in AI engineer jobs across District of Columbia.
- Bachelor's or master's degree in computer science, AI, data science, or a related field
- Active security clearance or eligibility for federal background investigation often required
- Proficiency in Python and machine learning frameworks such as TensorFlow or PyTorch
- Experience building and deploying models in cloud environments like AWS, Azure, or GCP
- Familiarity with responsible AI principles, model governance, and explainability practices
- Strong communication skills for presenting AI outputs to non-technical government stakeholders
AI Engineer Jobs in District of Columbia: Frequently Asked Questions
How do you become a ai engineer in District of Columbia?
There is no state-issued license required to work as an ai engineer in District of Columbia. Most employers in the region expect a bachelor's degree in computer science, mathematics, or a closely related field, with a master's degree preferred for senior roles. Because a large share of DC-area positions sit within federal contracting, obtaining or maintaining a security clearance is often the most critical credential. Building a portfolio of deployed models and contributing to open-source projects strengthens candidates without extensive industry experience.
Which companies hire ai engineers in District of Columbia?
District of Columbia ai engineer roles are posted by Booz Allen Hamilton, Humana, and Comcast and others right now, based on current listings on Migrate Mate as of July 2026. The region's concentration of federal agencies and defense contractors means many openings come from systems integrators and consultancies serving government clients rather than consumer technology companies.
Which District of Columbia cities have the most ai engineer jobs?
Washington and Pentagon are the District of Columbia areas with the most ai engineer openings. Washington DC itself drives the largest share of demand through federal agencies, think tanks, and government-focused tech firms, while nearby Northern Virginia suburbs like McLean and Rosslyn anchor major defense contractor campuses that concentrate additional AI hiring outside the district's boundaries.
Are there remote ai engineer jobs in District of Columbia?
Yes, and more than many fields. About 49% of ai engineer openings tied to District of Columbia are remote or hybrid as of July 2026, reflecting how much of the work involves writing code, training models, and analyzing data rather than on-site operations. Roles that require access to classified systems or secure government facilities are the primary exception and tend to require in-person work.
How can I get hired as a ai engineer in District of Columbia with little or no experience?
The most realistic entry path in DC is through a federal contractor's associate or early-career analyst program, where candidates build AI skills on government-funded projects. Firms like Booz Allen Hamilton and Leidos run structured early-career hiring pipelines that consider candidates with internships, academic research projects, or strong capstone portfolios. Adjacent roles such as data analyst, machine learning research assistant, or junior software engineer are common lateral entry points. Earning a cloud certification from AWS or Google strengthens an application considerably in this market.
Where can I find and apply to ai engineer jobs in District of Columbia?
You can find and apply to ai engineer jobs in District of Columbia on Migrate Mate, which lists current District of Columbia openings. Search the available roles, find the ones that match your background and preferences, and apply directly to whichever positions fit.
See All 58 AI Engineer Jobs in District of Columbia
Find roles in District of Columbia that match your experience and apply in just a few clicks.
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