Engineering and AI Specialist - Remote - Perm

**No sponsorship/C2C is available for this position**

Engineering and AI Specialist

Reports To: Director of Technical Delivery

Location: Remote

FLSA: Exempt

Job Summary

The AI Operations Specialist builds and runs the internal AI tooling, automations, and pilots that make AI a practical, everyday part of how Elevate Digital’s Engineering team delivers. Reporting to the Director of Technical Delivery, this role turns the AI operations roadmap into working software: maintaining agent pipelines and internal tools, testing new models and tools against real workflows, and keeping engineers unblocked as they adopt them.

This is an execution-focused role, not a standard-setting one. Direction, governance, and org-wide AI standards for Engineering remain owned by the Director of Technical Delivery; the AI Operations Specialist is the builder who makes that direction real, working alongside the Director on shared tooling projects rather than owning all of it independently.

Duties and Responsibilities

Tooling & Automation

• Build, maintain, and extend the AI tooling and agent pipelines Engineering relies on — including coding-agent integrations, MCP servers, and internal bots or scripts — working alongside the Director of Technical Delivery on shared tooling priorities.
• Keep existing automations reliable as models, APIs, and internal workflows change, monitoring for breakage and patching quickly.
• Maintain a lightweight, current catalog of what tooling is live, what’s experimental, and what’s been retired.

Pilots & Evaluation

• Run scoped pilots applying AI to specific internal workflows — ticket triage, documentation, code review assistance, onboarding, and similar — and report results back to the Director of Technical Delivery.
• Hands-on evaluation of new AI models, tools, and vendors as they emerge: what they’re good for, what they cost, and whether they fit Elevate’s delivery workflows.
• Track basic usage, cost, and quality signals for AI tooling so adoption decisions rest on evidence rather than hype.

Enablement & Support

• Support engineers adopting AI tooling day to day — answering questions, unblocking issues, and sharing practical techniques that actually work.
• Produce lightweight documentation, guides, or walkthroughs so internal tools are usable by people other than the person who built them.
• Surface friction, bugs, and gaps in existing tooling and pipelines back to the Director of Technical Delivery as input to the roadmap.

Required Competencies and Skills

• Builder Mentality: Genuine hands-on drive to build and ship internal tools and automations — this role is defined by making things, not evaluating them from the sidelines.
• AI/LLM Practical Fluency: Working knowledge of agentic workflows, prompt engineering, MCP, and RAG-style patterns, gained through real building rather than credentials alone.
• Automation & Scripting: Comfortable writing scripts, integrations, and lightweight pipelines to connect tools and remove manual work.
• Judgment Under Ambiguity: Able to size up a new tool or pilot quickly, form a point of view, and know when a decision needs to go to the Director of Technical Delivery rather than being made unilaterally.
• Documentation Habit: Writes clear, lightweight documentation as a habit, not an afterthought, so tools and pilots are usable by others.
• Collaborative Execution: Works well executing someone else’s roadmap and priorities on shared tooling projects, without needing to own the strategy to stay motivated.

Experience and Education

• Solid grounding in programming fundamentals — able to read, reason about, and debug the code and systems they build, not just accept AI-generated output at face value. This is not a “vibe coding” role.
• Demonstrated experience building automations, scripts, or AI-assisted tooling — through professional work, side projects, or hands-on experimentation. What you’ve built and can explain matters more than where you learned to build it.
• Practical, hands-on experience with agentic coding tools, AI coding assistants, or LLM-based pipelines, used deliberately rather than as a black box.
• Comfort operating in ambiguous, fast-changing technical territory where best practices are still being written.
• Self-taught and non-traditional paths are welcome, provided they come with real engineering fundamentals. Some formal computer science background…