Sr. AI Ops Engineer

Accenture Federal Services•Washington, DC

About The Position

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! The work: As a Senior AIOps Engineer, you will be the technical architect and senior implementer driving the client's AI Operations initiative.

Requirements

US Citizen or dual citizen (Public Trust eligible)
5+ years hands‑on experience in software engineering or DevOps
Expert Python programming (automation, frameworks, MCP servers)
Strong experience with API integrations and authentication (OAuth, PATs, IAM, SSO)
Advanced Git, CI/CD pipelines, and core AI/LLM concepts (prompting, embeddings, RAG, agents)
Proven ability to architect solutions and debug distributed systems
Technical leadership and mentorship abilities
Excellent documentation abilities and data‑driven mindset

Nice To Haves

Experience with Claude Code, MCP protocol, or similar AI developer tools
Deep AWS knowledge (Lambda, Bedrock, Knowledge Bases, S3, IAM, API Gateway)
Security architecture experience in regulated or government environments
Experience with Atlassian APIs, ServiceNow integrations
Open‑source contribution or maintainer background
Cloud or security certifications (AWS Solutions Architect, Azure, CISSP, CEH, etc.)
Experience with vector databases, semantic search, embeddings
Experience with Docker, Kubernetes, and containerized architectures

Responsibilities

Lead the architecture, design, build, and maintenance of the MCP (Model Context Protocol) ecosystem
Vet MCP servers for security, compliance, and functionality; build and optimize server configurations
Architect token optimization, performance tuning, and maintain MCP server catalog
Design, develop, and review secure AI skills, agents, and plugins
Establish a reusable skills library with standards, templates, and documentation
Lead RAG and AWS Knowledge Bases optimization, including embedding, chunking, retrieval testing, and taxonomy design
Develop and maintain governance structures, security reviews, vetting processes, and compliance frameworks
Ensure IAM, authentication, and authorization requirements are met
Troubleshoot complex MCP, skills, agent, and environment setup issues
Maintain support documentation and perform root cause analyses
Lead onboarding, demos, and technical enablement for AI tools (Claude Code, MCP, AWS AI stack)
Evaluate new AI platforms and design proof‑of‑concepts
Provide senior technical implementation support for AI projects and automation frameworks