AI Engineer

• Own the architecture, technical direction, and engineering standards for the Workforce AI-enabled enterprise platform and its microservices
• Define and document service boundaries, API contracts, data flows, integration patterns, and key technical decisions
• Lead the design of AI-enabled architecture, including tool calling, system instructions, context management, prompt and control flow, and LLM service integration
• Design secure enterprise integrations for identity, document workflows, collaboration tools, and external APIs
• Manage technical debt, platform risk, and architectural drift
• Lead technical execution through solution design, task breakdown, estimation, sequencing, and code review
• Partner with the Product Manager to translate product goals and requirements into technical designs, milestones, and engineering work
• Establish standards for code quality, automated testing, documentation, and definition of done
• Mentor engineers through design reviews, pairing, code reviews, and technical feedback
• Serve as the primary technical contact for engineering leadership, product, and customer stakeholders
• Serve as Release Manager for the multi-service release train, coordinating release readiness, notes, and records
• Represent the team in change control and release review processes, presenting changes, risks, and rollback plans
• Own production posture, including rollback decisions, incident triage, root cause follow-through, and post-release verification
• Collaborate with platform and DevOps engineers on CI/CD, Helm deployments to AKS, observability, autoscaling, and performance testing
• Contribute directly to feature implementation, critical-path work, integration work, and production fixes
• Build and maintain full-stack capabilities across modern web front ends and backend web APIs

Software Architect – AI-Enabled Enterprise Platform

• Design, develop, test, deploy, and support production-grade AI agents and AI-enabled applications
• Build agent architectures incorporating orchestration, tool use, state management, error handling, evaluation, observability, and operational support
• Integrate mission and enterprise data with large language models using RAG, MCP, secure tool access, prompt management, and context engineering
• Incorporate geospatial intelligence data, including raster and vector data, spatial context, metadata, and analytic results, into applications and user workflows
• Develop Python, SQL, R, and RESTful services connecting AI capabilities with enterprise data platforms
• Develop Node.js applications, dashboards, and user interfaces that securely consume Oracle Database data
• Collaborate with technical and mission stakeholders to translate requirements into secure, maintainable, and usable AI-enabled solutions
• Move AI capabilities from early prototypes to production
• Collaborate with engineers, data specialists, security professionals, and mission stakeholders

• Lead the technical design, development, testing, deployment, and sustainment of AI agents and AI-enabled applications
• Define agent architectures incorporating orchestration, tool use, state management, error handling, evaluation, observability, and operational support
• Lead integration of mission and enterprise data with large language models using RAG, MCP, secure tool access, prompt management, and context engineering
• Guide development of Node.js applications, dashboards, and user interfaces that securely consume Oracle Database data
• Oversee integration of geospatial intelligence data, including raster and vector data, spatial context, metadata, and analytic results
• Establish engineering practices and review technical products
• Mentor developers and promote consistent approaches across the team
• Coordinate technical delivery across mission, data, cloud, security, database, and customer stakeholders
• Provide hands-on technical leadership across AI agents, applications, data integration, and cloud technologies
• Help establish architecture direction and coordinate stakeholders
• Keep delivery focused on meaningful outcomes

AI Engineer – Technical Manager

• Train, test, deploy, and maintain models that learn from data
• Define the direction of critical AI solutions
• Apply best-fit machine learning algorithms and technologies
• Support enterprise-wide application and data capabilities
• Process data and information at massive scale
• Collaborate with data engineers, data scientists, solutions architects, and MLOps engineers
• Guide clients on AI/ML algorithms, tools, and frameworks
• Help define AI strategy for national security customers

• Design, develop, test, and maintain AI agents and generative AI applications using Python
• Develop agent workflows using large language models to interpret requests, reason across multiple steps, select tools, retrieve information, and generate grounded responses
• Design, test, and refine prompts, task instructions, few-shot examples, response formats, and other prompt-engineering components
• Develop agent orchestration logic including state management, context management, tool selection, multi-step execution, retries, exception handling, and recovery
• Develop Python components using boto3, botocore, SDKs, and supporting libraries
• Integrate agents with tools, APIs, MCP services, databases, knowledge sources, and enterprise applications
• Build and optimize retrieval-augmented generation capabilities
• Implement structured outputs, schema validation, response validation, guardrails, and error handling
• Develop reusable Python libraries, utilities, agent components, prompts, and development patterns
• Create automated unit, integration, regression, and AI evaluation tests
• Analyze model and agent behavior to identify and correct performance or reliability issues
• Compare and evaluate models, prompting approaches, retrieval strategies, and agent designs
• Translate business problems into AI use cases, expected behaviors, acceptance criteria, and measurable outcomes
• Support demonstrations, user testing, defect resolution, production validation, monitoring, and continuous improvement
• Maintain source code, prompts, technical designs, configuration, evaluation criteria, and documentation
• Participate in code reviews, architecture discussions, backlog refinement, demonstrations, testing, release readiness, and Agile/SAFe delivery activities
• Perform other duties as assigned

AI Developer, Python

• Lead the architecture, development, and delivery of cloud, data, process intelligence, and AI solutions
• Architect, implement, and operate cloud-native services on AWS, including API Gateway, Lambda, Fargate, DynamoDB, SQS, S3, KMS, IAM, and CloudWatch
• Build data ingestion, transformation, and API components for large-scale, multi-source data platforms
• Develop and extend Celonis solutions, including Data Connections, Data Integration transformations, object-centric data models, event logs, Knowledge Models, PQL metrics, Studio Views, and Action Flows
• Design and build agentic AI workflows using Amazon Bedrock, Azure OpenAI, and Celonis AI capabilities
• Own system architecture and technical direction for Innovation Lab products
• Lead end-to-end technical delivery of the A-123 Continuous Controls Monitoring solution and additional Innovation Lab products from prototype through production deployment
• Package solutions for reuse across federal agencies through parameterized configuration, automated deployment, versioning, and reference architectures
• Support capability demonstrations and post-award implementation activities, including source system mapping, environment configuration, and deployment into agency and FedRAMP-authorized cloud environments
• Collaborate with Celonis and AWS partner engineering teams on solution certification, marketplace listings, and partner program requirements
• Establish scalable engineering practices that improve reliability, data accuracy, deployment efficiency, and rapid deployment for new agency environments
• Reduce manual control testing, audit, and review hours and increase adoption of Innovation Lab solutions across client engagements, demonstrations, and proposals

AI Engineer jobs in Virginia

Software Architect – AI-Enabled Enterprise Platform

AI Engineer

AI Engineer – Technical Manager

AI Engineer

AI Developer, Python

Senior Cloud, Data & AI Engineer