Agentic AI/DevSecOps Engineer
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Agentic AI/DevSecOps Engineer
Location
Hybrid, Columbia, MD, 21046, USA
Experience
Mid
Posted
Jul 14, 2026
Apply by
August 13, 2026
Applicants
0
Early applicantEasy applyFull-timeHybrid
Job Description
## Description
Title: Agentic AI and DevSecOps Engineer
Location: Hybrid in Columbia, MD
Clearance: Must be able to obtain and maintain a High-Risk Public Trust
Company Overview
At APV, we’re more than a technology company — we’re a mission-driven powerhouse transforming organizations through advanced technology and human ingenuity. Our expertise spans AI/ML, data architecture, low-code/no-code development, Agile DevSecOps, and cloud services, delivering scalable and meaningful solutions.
In our Emerging Technology Lab, innovation drives progress. Our teams create intelligent chatbots, AI-powered assistants, robotic process automation (RPA), essay graders, and data analytics platforms. If you’re passionate about solving complex challenges and shaping the future, APV is the place for you. Since 2007, we’ve partnered with federal and state agencies to deliver IT, training, and consulting solutions that achieve mission-critical outcomes. Built on accountability, integrity, and quality, we go beyond expectations. With 70+ prime contracts and a proven record of client success, APV continues to grow — and we’re looking for exceptional talent to grow with us.
At APV, we Always Provide Value
SUMMARY
We are seeking a highly skilled and hands-on Agentic AI/DevSecOps Engineer to join our dynamic team. The ideal candidate will be collaborative, innovative, and capable of providing effective AI solutions for various internal and federal projects.
This role requires a deep understanding of legacy applications, emerging technologies, AI technologies, strong problem-solving skills, and the ability to work closely with cross-functional teams.
DUTIES
Agentic System Design & Development
· Design and build Agentic AI systems using frameworks such as LangChain, Lang Graph, MCP, or similar
· Develop multi-agent or task-oriented architectures for autonomous workflows
· Integrate AI agents with enterprise APIs, data platforms, and external tools
· Define agent workflows, orchestration logic, and tool-use strategies
· Evaluate when to use LLM-based vs traditional approaches
AI Engineering & Data Systems
· Build RAG pipelines using embeddings and vector databases
· Implement vector search and retrieval strategies for knowledge-based agents
· Work with structured and unstructured data for AI-driven applications
· Apply AI/ML fundamentals to improve agent reasoning and performance
Testing, Evaluation & Optimization
· Develop testing and evaluation pipelines for agentic workflows and LLM systems
· Implement unit and integration testing for AI-enabled systems
· Optimize systems for accuracy, latency, cost, and reliability
· Validate and monitor AI outputs for quality and consistency
Deployment, DevSecOps & Infrastructure
· Implement secure DevSecOps pipelines for AI applications
· Deploy solutions in AWS cloud environments
· Build and manage infrastructure using IaC tools
· Work with containerized applications (Docker/Kubernetes)
· Ensure systems meet security and compliance requirements (especially federal environments)
General Responsibilities
· Deliver production-grade, scalable AI agent solutions
· Support Agile development practices and iterative delivery
· Document architecture, workflows, and decisions
· Stay current with advancements in Agentic AI and LLM technologies
EDUCATION
· Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field
REQUIRED QUALIFICATIONS
· 1–2 years of hands-on experience implementing or deploying Agentic AI solutions
· 3+ years of Agile software development and DevSecOps experience
· Experience building AI/ML-enabled systems, including LLM-based applications
· Experience implementing Infrastructure as Code (IaC)
· Strong programming skills in Python (primary); JavaScript (preferred)
· Working knowledge of:
o Linux environments
o SQL and relational databases
o Vector databases
· Must be able to obtain and maintain a High-Risk Public Trust or equivalent federal client access. This role supports sensitive federal programs and involves elevated access to systems and data.
· Position requires the current ability to obtain and maintain required access without interruption in alignment with long-term program needs.
· Must be authorized to work in the United States without employer sponsorship now or in the future.
PREFERRED QUALIFICATIONS
· AWS Certification ie (Solutions Architect)
· Experience deploying AI/ML solutions in federal or regulated environments
· Experience with:
o RAG architectures and retrieval optimization
o Multi-agent systems and orchestration workflows
o AI system evaluation and observability
ABOUT APV
APV is an Equal Employment Opportunity employer. All qualified applicants are considered without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, or marital status.
Key Responsibilities
- Design and build Agentic AI systems using frameworks like LangChain, Lang Graph, and MCP
- Develop multi-agent or task-oriented architectures for autonomous workflows
- Integrate AI agents with enterprise APIs, data platforms, and external tools
- Build RAG pipelines using embeddings and vector databases
- Implement vector search and retrieval strategies for knowledge-based agents
- Develop testing and evaluation pipelines for agentic workflows and LLM systems
- Implement secure DevSecOps pipelines for AI applications
- Deploy solutions in AWS cloud environments
- Build and manage infrastructure using IaC tools
- Ensure systems meet security and compliance requirements for federal environments
Requirements
- Bachelor’s degree in Computer Science
- Engineering
- Data Science
- Mathematics
- or a related technical field
Skills Required
PythonJavaScriptLangChainLang GraphMCPRAGVector databasesSQLLinuxAWSDockerKubernetesInfrastructure as CodeAgileDevSecOpsLLMProblem solvingCollaborationInnovationRAG architecturesMulti-agent systemsAI system evaluationObservability
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