Agentic Automation Consultant

Agentic Automation Consultant
Location: Remote/US-based
Contract Details: 3 month contract, with possibility of extension
Rate: $80-100/hr

About Mind Moves

Mind Moves is a women-owned Washington, D.C.-based firm helping businesses and governments to embrace, build and deploy ‘human in the loop’ Artificial Intelligence (AI) solutions to elevate mission and value. We are pioneers with deep expertise in the field of machine learning and AI. We have delivered responsibly developed products and services that impact millions of users worldwide, while generating millions of dollars in revenue. We have worked with Fortune 500 corporations and large government entities in health care, supply chain management, financial services and life sciences. We apply a structured methodology and holistic approach to AI transformation and a broad spectrum of technical services centered in the harnessing of people, science and technology.

The Role

We’re looking for an Agent Automation Consultant to design, build, and deploy AI agents that automate Mind Moves’ internal operations. This is not a role where you use AI to work faster - it’s a role where you build AI that does the work and recursively improves.

You’ll take operational workflows - contractor onboarding, staff time allocation, subcontract reviews, market-rate research, process documentation, and more - and decompose them into agent architectures: skills, tools, evals, memory, and orchestration layers that run with minimal supervision and get better over time.

We’re a small team and you’ll have real autonomy. Your job is to take Mind Moves from “AI-assisted operations” to “agent-operated operations”.

This is a fixed-term contract focused on standing up the foundational layer: identifying the highest-leverage workflows, building the first generation of agents, and leaving behind reusable infrastructure and documentation the team can build on.

What You’ll Do:

• Build AI agents from scratch that autonomously run internal operations workflows, including but not limited to:
• Staff time allocation and utilization tracking across multiple contracts/projects
• Subcontractor agreement review and version control against active contracts
• Onboarding for W-2 employees and 1099 contractors
• Market-rate research, with a focus on government contracting benchmarks
• Operational process documentation and compliance tracking
• Business development bids, proposals and solicitation responses
• Internal workflow instruction and technical documentation
• Break workflows down into the components agents actually need: skills, tools, evals, guardrails, memory and feedback loops.
• Build evaluation frameworks that measure agent quality, catch regressions and drive improvement without someone babysitting the system.
• Design self-improving loops. Agents should monitor their own outputs, learn from outcomes, and get sharper over time. The bar: it works at 3am on a Sunday and is better by Monday.
• Own everything from identifying which workflows to automate, to prototyping, to deployment, to monitoring and iteration.
• Build reusable agent infrastructure, internal tooling and documentation so the rest of the Mind Moves team can operate and trust what you’ve built.
• Stay plugged into the frontier of agentic AI - new model capabilities, tool-use patterns, multi-agent orchestration, MCP, evals frameworks - and bring what you learn into production fast.

You’ll Thrive If You

• Can mock up an MVP and then go build the thing. You scope what matters, why, and then ship it yourself.

• Are extremely AI-pilled. You have strong opinions on tool-use vs. code-gen agents, when to use RAG vs. fine-tuning, and how to build evals that matter.
• Think in systems and loops, not tasks and tickets. You want to design processes where agents trigger other agents, outputs become inputs, and the whole system compounds without someone pressing “run.”
• Have built and shipped agents in production — real systems that ran on their own, handled edge cases, and got better over time.
• Know the difference between a cool demo and a reliable agent is evals, observability, structured outputs, error handling and constant iteration on failure modes.
• Experiment fast and cheap. You validate agent architectures with quick tests before sinking time into production builds.
• Are fluent across the modern AI stack without being religious about any of it.
• Communicate clearly and own your work…