AI Ops Engineer
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About the Role
The work:
Key Responsibilities:
MCP Ecosystem Support
- Test MCP servers for functionality and security checks
- Configure server instances using established patterns
- Maintain server catalog documentation
- Troubleshoot basic connection issues and escalate when needed
- Learn MCP protocol internals and best practices
Skills & Agents Development
- Develop basic skills for client workflows under guidance
- Test team‑submitted skills for quality
- Maintain skills library documentation
- Contribute to starter templates and samples
- Learn secure coding practices
AWS Knowledge Bases & RAG Testing
- Run retrieval quality tests
- Assist with content tagging and classification
- Document test results and accuracy metrics
- Support documentation for RAG interactions
- Learn embeddings and RAG optimization
Governance & Security
- Follow marketplace vetting processes
- Conduct basic security reviews
- Maintain version control and audit trails
- Document security patterns
- Learn security best practices for AI tooling
Technical Support
- Provide first‑line debugging for MCP, skills, and agents
- Assist with environment setup
- Resolve common configuration issues
- Maintain support documentation and FAQs
- Document issues and resolutions
Training & Enablement
- Support onboarding to Claude Code and AI tooling
- Maintain best‑practice docs
- Assist with demos and sessions
- Maintain sandbox environments
- Create tutorials and how‑to guides
Platform Evaluation & Project Support
- Test emerging AI platforms
- Assist with demos and proof‑of‑concepts
- Document results and user feedback
- Test integrations with systems like JIRA, Confluence, CMDB
- Support AI project implementation
- Collect adoption metrics and usage data
Here is what you need:
- US citizen or dual citizen (Public trust eligible)
- 1+ years in software engineering, DevOps, or ITBasic
- Python skills (scripting, APIs, JSON/data manipulation)
- Familiarity with APIs and authentication (keys, tokens)
- Basic Git proficiency and understanding of AI/LLM concepts
- Strong troubleshooting ability
- Solid communication and willingness to learn
- Ability to work collaboratively and ask clarifying questions
- Strong attention to detail and documentation habits
Preferred experience:
- Active Secret or Public Trust clearance
- Exposure to Claude Code, AI dev tools, or LLM platforms
- Basic AWS knowledge (S3, Lambda, IAM)
- Experience in government or regulated environments
- Familiarity with JIRA and Confluence
- Interest in open‑source or personal coding projects
- Agile/Scrum exposure
- Certifications (AWS Cloud Practitioner, Security+, etc.)
As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Washington, Vermont, the District of Columbia, and the city of Cleveland. The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply.
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