DevOps Artificial Intelligence Engineer

ManTech • Ashburn, VA

12d • Hybrid

About The Position

Transform the future of federal services with MANTECH! Join a vibrant, energetic team committed to enhancing national security and public services through innovative tech. Since 1968, we've partnered with Federal Civilian sectors to deliver impactful solutions. Engage in exciting projects in Digital Transformation, Cybersecurity, IT, Data Analytics and more. Ignite your career and drive change. Your journey starts now—innovate and excel with MANTECH! MANTECH seeks a motivated, career- and customer-oriented SME AI Ops Engineer to join our AI innovation team in Ashburn, VA . This is currently a hybrid position with 2-3 days onsite/week. Each day U.S. Customs and Border Protection (CBP) oversees the massive flow of people, capital, and products that enter and depart the United States via air, land, sea, and cyberspace. The volume and complexity of both physical and virtual border crossings require the application of solutions to aid officers in detecting threats while promoting efficient trade and travel.

Requirements

• BS/BA and 12+ years or MS/MA/MBA and 9+ years or PhD/Doctorate and 7+ years.
• Experience in Data Engineering, DevOps, or AI/ML Ops roles.
• Strong coding skills in Python or Java.
• Hands-on experience with vector search and retrieval-augmented generation (RAG), containers and orchestration (Docker, Kubernetes).
• Knowledge of CI/CD pipelines (Harness, Jenkins) and best practices for AI/ML deployment, security, compliance, and access controls for data and AI systems.
• Deep understanding of search, indexing, and graph databases (Elasticsearch, Neo4j, Janusgraph or equivalent).
• Experience with LLM deployment frameworks (LangChain, RAG pipelines, vector databases like Pinecone, Weaviate, or FAISS).

Nice To Haves

• Prior experience managing LLM workloads at scale (fine-tuning, serving, and monitoring).
• Familiarity with Agentic architecture and Model-Context-Protocol (MCP).
• Experience with GPU-based infrastructure and performance optimization.
• Familiarity with database (Postgres) schema and tables.
• Exposure to observability for AI models (model drift, bias detection, explainability).

Responsibilities

• Lead the design and operational deployment of Large Language Model (LLM) based applications and AI agents across AWS or Google cloud environments.
• Implement and optimize Model Context Protocol (MCP) for context-aware orchestration and efficient scaling of AI services.
• Design and manage embeddings generation, storage, and retrieval, enabling semantic search and recommendation and develop monitoring, logging, and observability solutions leveraging the Elastic Stack (Elasticsearch, Logstash, Kibana).
• Engineer graph-oriented deployment architectures for dependency mapping, relationship-aware data flow advanced troubleshooting and automate deployment, scaling, and monitoring using modern MLOps and AIOps practices (CI/CD, containerization, orchestration).
• Ensure data quality, lineage, and governance across multiple systems and pipelines
• Collaborate with data scientists, ML engineers, and DevOps teams to deliver high-availability AI-powered applications.
• Build monitoring and alerting solutions to detect anomalies, performance bottlenecks, and failures in AI/ML services and research and implement emerging AI infrastructure and tools and best practices to continuously improve system reliability and scalability.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees