AI Architect – Technical Lead

Salary Range: 200000 to 230000 (Currency: USD) (Pay period: per-year-salary)

hatch I.T. is partnering with Expression to find an AI Architect (Technical Lead). See details below:

About The Role:

Expression is seeking an experienced AI Architect to serve as Technical Lead designing and technically integrating advanced Artificial Intelligence (AI) and Large Language Model (LLM) capabilities supporting the Department of Homeland Security (DHS).

This role will support the development and integration of secure, mission-focused AI agents within the DHS AI environment. The selected candidate will lead the adaptation of multi-agent AI capabilities, including intelligent workflow orchestration, retrieval-augmented generation (RAG), model evaluation, and governed enterprise data integration, to enhance investigative analysis, information retrieval, report generation, and human decision support.

The ideal candidate is a hands-on AI architect and technical leader with extensive experience designing and delivering enterprise AI applications. You are equally comfortable defining system architecture, developing and reviewing production-quality software, integrating LLMs with enterprise data systems, and mentoring engineers through complex technical challenges.

This position requires a strong understanding of modern AI engineering, distributed application architectures, secure API development, and responsible AI deployment within highly regulated environments. You will work closely with AI engineers, data engineers, program leadership, and Government stakeholders to deliver reliable, explainable, secure, and scalable AI capabilities.

Location and Clearance:

• Clearance: Top Secret/SCI required 

• Location: Shirlington, VA

About the Company:

Founded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression’s “Perpetual Innovation” culture focuses on creating immediate and sustainable value for their clients via agile delivery of tailored solutions built through constant engagement with their clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review.

Responsibilities:

Lead the technical architecture, design, and implementation of enterprise AI and agentic AI solutions within the Government's existing AI environment, emphasizing reuse of approved infrastructure, services, and model endpoints.
Define scalable, secure, and maintainable software architectures integrating LLMs, specialized AI agents, enterprise data services, APIs, and human-in-the-loop workflows.
Design and implement multi-agent orchestration frameworks, including Responder–Evaluator–Reporter workflows, model selection, prompt management, tool invocation, and structured output validation.
Lead the integration of Government-approved frontier AI models through authorized endpoints, ensuring appropriate model configuration, version management, performance evaluation, and controlled execution.
Architect retrieval-augmented generation (RAG) solutions that integrate authorized enterprise data sources while preserving source attribution, access controls, data lineage, and traceability.
Guide integration with Palantir, Databricks, Elasticsearch, and other approved Government data services through secure APIs and governed interfaces.
Design secure AI agent execution frameworks incorporating identity propagation, role-based and purpose-based access controls, bounded tool permissions, approval checkpoints, execution limits, and safe failure mechanisms.
Develop and review production-quality backend services, APIs, and orchestration components using Python and modern software engineering practices.
Lead architecture and code reviews, resolve complex integration challenges, and establish engineering standards for maintainability, reliability, security, and performance.
Design evaluation and testing approaches for LLM and multi-agent applications, including factual accuracy, consistency, explainability, latency, scalability, and computational cost.
Establish observability, logging, prompt and model version tracking, and auditability across AI workflows, ensuring AI-generated outputs can be traced to supporting sources and reviewed by authorized personnel.
Collaborate with cybersecurity, DevSecOps, privacy, and Government stakeholders to align system designs with approved deployment pipelines, security controls, authorization requirements, and release processes.
Support the adaptation of existing AI algorithms, prompts, and software components into Government-approved investigative workflows, documenting technical lineage, modifications, and integration requirements.
Produce solution architecture documents, system design specifications, interface control documents, data-flow diagrams, technical evaluations, and engineering implementation guidance.
Support technical demonstrations, prototype evaluations, user acceptance activities, and Government design reviews.
Provide technical leadership and mentorship to AI engineers and data engineers while maintaining meaningful hands-on involvement in architecture, development, debugging, and integration.
Evaluate proposed third-party AI tools, frameworks, and software components for technical suitability, security implications, integration complexity, and reuse of existing Government capabilities, coordinating recommendations through established approval processes.

Qualifications:

Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Artificial Intelligence, or a related technical field, or equivalent relevant professional experience.
12+ years of professional experience in software engineering, AI engineering, data engineering, or enterprise application development, including 3+ years in software architecture or technical leadership roles.
Demonstrated hands-on experience architecting, developing, and deploying enterprise LLM-powered and generative AI applications, including agentic AI workflows, multi-agent orchestration, and retrieval-augmented generation (RAG).
Experience designing and implementing multi-agent AI systems using frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, or equivalent technologies, including Responder–Evaluator–Reporter workflows, model comparison, and AI output verification.
Experience with LLM prompt engineering, prompt version management, structured generation, tool/function calling, agent execution controls, and human-in-the-loop workflows.
Strong Python software engineering skills, including RESTful API development, asynchronous programming, modular application design, and modern software development practices.
Experience designing distributed applications, microservices, or event-driven architectures and integrating AI capabilities with structured and unstructured enterprise data through secure APIs and retrieval architectures.
Experience implementing secure, permission-aware enterprise data integrations, including authentication, authorization, identity propagation, data governance, source traceability, and auditability.
Experience designing and evaluating reliable, explainable AI systems, including factual grounding, source citations, hallucination mitigation, model performance evaluation, and responsible human oversight.
Experience with LLMOps and AI assurance practices, including automated regression testing, prompt-injection defenses, model/prompt version tracking, application observability, and performance monitoring.
Experience with cloud-native architectures and containerized application deployment using Docker, AWS or Azure, Kubernetes, Terraform, Helm, or comparable technologies.
Experience implementing CI/CD pipelines, automated testing, version control, and software configuration management to support secure, reliable application delivery.
Demonstrated ability to translate technical and mission requirements into scalable system architectures, implementation plans, interface specifications, and engineering deliverables.
Experience leading technical design and code reviews, troubleshooting complex software integrations, mentoring engineers, and providing hands-on technical guidance throughout the software development lifecycle.
Strong written and verbal communication skills, including experience producing technical documentation, presenting architectural decisions, and supporting technical demonstrations, Government acceptance testing, and operational pilot deployments.

Preferred Qualifications:

Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related technical discipline.
Experience integrating enterprise AI applications with Palantir, Databricks, Elasticsearch, or similar governed data and analytics platforms.
Experience developing Python backend services using FastAPI, Pydantic, asyncio, or comparable frameworks.
Experience supporting secure software development and deployment in Federal Government, Department of Defense, Intelligence Community, or Department of Homeland Security environments.
Familiarity with Government cybersecurity, privacy, accessibility, and software authorization processes.
Experience adapting existing AI research, algorithms, prototypes, or software components into operational enterprise applications.
Experience supporting AI-enabled document processing, intelligent search, case management, investigative analytics, or automated report generation.