Analyst, AI Enablement & Value Creation

Machinify•Dallas, TX

2d•Onsite

About The Position

The Analyst, AI Enablement & Value Creation works in Machinify’s Transformation Office alongside the Director, Value Creation & Integration and the Chief Transformation Officer. The role executes the company’s AI enablement strategy across back-office departments, taking initiatives from initial opportunity identification and scoping through deployment and measurement of realized value. It also brings structure to initiatives already underway elsewhere in the company. The position combines hands-on AI solution development, project leadership, and value measurement. The Analyst builds AI skills, integrations, agents, and automated workflows; maps processes and develops department deployment plans; and coordinates department teams, vendors, and partners. The role defines success criteria before work begins, develops dashboards and measurement systems for adoption, utilization, and impact, and ties initiatives to measurable business outcomes. The Director owns strategy, department priorities, governance, approvals, and blocker removal; the Analyst runs day-to-day execution and is accountable for results. The role is based on-site in Machinify’s Dallas, Texas office, co-located with the Director. Travel is occasional for department on-sites and leadership meetings. The program may require flexibility outside standard business hours at times. The listed salary range is $80,000–$85,000, with compensation dependent on candidate-specific factors and role level.

Requirements

Two to four years of professional experience in analytics, consulting, operations, product, or an engineering-adjacent role.
Experience taking a project with multiple contributors from inception to delivery.
Project management capability across initiation, scoping, planning, team and vendor coordination, issue escalation, and execution against a plan, with examples to discuss.
Current hands-on fluency with Claude Code, Claude Cowork, and Claude Chat, plus working exposure to OpenAI Codex, Google Antigravity, and other AI tools; must be able to demonstrate something built.
Working understanding of skills, MCP connections between models and systems, and agentic frameworks for orchestrating multi-step work.
Process-mapping experience, including documenting current state, identifying automation candidates, and designing future state.
Analytical ability to define success metrics, obtain supporting data, and present results to department leaders.
Working knowledge of at least one scripting language; Python or JavaScript preferred.
Clear written communication, including the ability to brief an executive concisely and train a department in an hour.
Bachelor’s degree or an equivalent combination of education and demonstrated AI build experience.
Ability to work on-site in the Dallas, Texas office.
Ability to accommodate flexibility outside standard business hours at times.

Nice To Haves

Experience managing third-party vendors or implementation partners through a software or automation rollout.
Experience defining KPIs and building dashboards in Power BI, Excel, or a similar tool.
Experience creating training content or running enablement sessions for non-technical teams.
Healthcare, payment integrity, or revenue cycle exposure.
Private equity-backed company experience or exposure to post-acquisition integration and value creation work.
Experience with Notion, Slack, Jira, Salesforce, or Smartsheet, including building integrations or automations on them.

Responsibilities

Define AI enablement success metrics for adoption, utilization, and impact; build and own the related dashboards and measurement systems, including a monthly productivity survey correlated with utilization data.
Tie each initiative to measurable outcomes such as hours returned, cycle time reduced, cost avoided, or revenue protected, and track AI spend by initiative and department.
Move initiatives through the value-capture lifecycle from Pipeline through Banked-in-P&L, documenting evidence at each stage; prepare analysis and narrative while Finance owns the numbers.
Produce the AI Enablement section of monthly Executive Leadership Team materials and support Board materials during peak cycles.
Map current-state departmental processes, identify steps AI can remove or compress, and translate findings into skill checklists and deployment plans with named owners and dates.
Run department deployments end to end, including setup sessions, office hours, training, and adoption tracking against a baseline.
Maintain AI training materials, the skills library, and other self-service onboarding assets as tools change.
Deploy solutions using Claude tooling, third-party AI applications, and non-AI vendor platforms; own vendor relationships from scoping and proof of concept through contracting support, rollout, and results tracking.
Launch initiatives by identifying opportunities with departments, writing charters and success criteria, defining scope, creating plans, and running kickoffs.
Own day-to-day initiative execution, including cadence, RAID logs, open-item closure, and delivery against plans.
Coordinate with Finance, Operations, Client Success, Legal, Sales, Implementations, other back-office functions, and external vendors and partners to secure required inputs, decisions, and time.
Escalate exceptions to the Director with the issue, options, and a recommendation; organize the portfolio so each initiative has a charter, owner, stage, and next milestone.
Collect departmental feedback and turn it into prioritized change requests; serve on the weekly AI Enablement steering committee and help prepare agendas, metrics, decisions, and follow-ups.
Build and document Cowork folder structures, Claude skills, Claude Code utilities, MCP connections, and automated workflows so solutions can be handed off.
Build agents where needed in Claude or in agent builders within deployed platforms, such as Within, connecting them to systems departments already use.
Recommend solutions for department needs, including training, Claude skills, internal builds, or third-party tools, and evaluate vendor options and trade-offs.
Verify AI-assisted output before it reaches a department or executive, ensuring numbers are sourced.
Work toward the stated milestones: learn the program and propose metrics within 90 days; deliver at least two end-to-end department deployments and launch a weekly-reviewed dashboard by six months; and deliver deployments across multiple departments with evidence-backed value reporting by twelve months.