Job Summary

The Head of AI Transformation is responsible for fundamentally rethinking how our business operates—across estimating, finance, operations, design workflows, sales operations, tooling, reporting, and communication—by applying practical, production-grade AI. The Head of AI Transformation will systematically identify where AI can automate work, eliminate redundant tools, compress cycle times, improve decision quality, and expand margin. This role is not about incremental improvement - it is about reimagining systems, workflows, and decision-making using AI—often replacing existing tools, processes, and assumptions entirely. This role operates independently but works collaboratively across all functions, with direct access to the CEO, and the mandate is to question everything.

Responsibilities

Discovery & Diagnosis

• Rapidly audit how Outform operates across estimating, finance/reporting, sales ops, design workflows, project management, manufacturing interfaces, and delivery.
• Map manual work, repetitive decisions, tool overlap, spreadsheet dependencies, and failure points at scale.
• Produce an AI Opportunity Map with ranked opportunities by speed-to-impact, ROI, and risk.
• Maintain a Kill List of tools, workflows, and reports to eliminate or replace.

Build & Automate

• Prototype and deploy AI-powered solutions including internal tools, automations, agent-based workflows, and lightweight services that can evolve into production systems.
• Facilitate and/or oversee the replacement of legacy workflows, scripting away manual/repetitive steps and consolidating or removing redundant software.
• Demonstrate a bias to action: favor working software and measurable value over decks and prolonged consensus-building.

Operate, Scale & Systemize

• Move pilots into production with simple, supportable runbooks; instrument solutions for reliability, observability, and maintainability.
• Define a pragmatic AI Operating Model (where AI is mandatory; where humans remain in the loop).
• Establish lightweight internal standards for prompt/version management, data handling, and credential security; partner with technology leaders without becoming dependent on them.

Adoption & Change Enablement

• Introduce new ways of working (not just new tools) with concise SOPs, training, and quick guides.
• Capture before/after metrics, publish wins, and foster a builder culture across teams.
• Challenge legacy assumptions respectfully but directly; operate across org boundaries without being bound by them.

Measurement & Economics

• Tie every initiative to business outcomes: hours eliminated, cycle-time reduction, cost savings/avoidance, margin expansion, and accuracy lift.
• Maintain a live portfolio of initiatives with clear ROI, scale potential, and sunset criteria.

Success Metrics (KPIs)

Core (non-negotiable)

• Hours eliminated/automated per month (baseline → trend)
• Cycle time reduction for key flows (e.g., estimating, approvals, reporting)
• Cost savings / cost avoidance (verified by Finance)
• Margin improvement driven by faster, better decisions
• Tools eliminated or consolidated (license count and spend reduced)

Secondary

• Accuracy improvements (e.g., pricing, forecasting error reduction)
• Reduction in manual errors and rework
• Adoption rate and weekly active use of AI-enabled workflows
• Idea → production lead time (mean/median)

Qualifications:

Education

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Design Engineering, or related field or equivalent, demonstrable experience building and shipping internal tools/automations.
• Advanced degree welcome but not required; evidence of hands-on capability is paramount.

Experience

• 5+ years in roles such as AI Engineer, Technical Founder, Head of Systems/Internal Tools, Automation Architect, AI Product Lead, or similar—preferably in startup/scale-up or founder-led environments.
• Proven track record building (not only advising on) internal tools, LLM-powered automations, and/or agent-based workflows from scratch and moving them to production.
• Experience replacing or bypassing traditional systems (e.g., ERP modules, estimating tools, finance/reporting stacks, PM software) with leaner, AI-augmented flows.
• Demonstrated ability to ship quickly, iterate, instrument, and measure value in real terms.

Knowledge (Tools & Domains)

• Hands-on with LLMs (commercial and open-source), prompt engineering/versioning, retrieval-augmented generation, and basic vector search concepts.
• Comfortable with no-/low-code and workflow automation (e.g., Retool, Bubble, Airtable, Zapier, n8n) and/or scripting with Python/JavaScript; APIs, webhooks, and OAuth.
• Familiarity with agent frameworks, light RPA, and orchestration libraries; basic data engineering patterns (batch vs. event-driven; connectors; ETL/ELT).
• Practical appreciation of security, privacy, and data boundaries (least privilege, secret management, PII handling) framed as enablers rather than blockers.
• Working knowledge of version control (Git), basic containerization or packaging, and simple deployment approaches.

Abilities

• Rapid process mapping and decomposition; identify high-ROI “thin slices” for automation.
• Business case & ROI modeling that Finance can audit; metric design and instrumentation.
• Strong product sense: usability, lightweight adoption paths, and “minimum lovable” tools.
• Influence without authority; clear written and verbal communication with frontline teams and executives.
• Operate independently in ambiguity; prioritize ruthlessly; balance speed with safety.
• Challenge assumptions constructively; comfort “breaking” legacy ways of working when economics support it.

Core Competencies & Personal Characteristics:

• Builder Mindset & Bias to Action – ships working software and iterates.
• Systems Thinking – sees across tools, teams, and data flows to simplify.
• Problem Solving & Analytical Rigor – frames hypotheses, tests, measures.
• Collaboration & Influence – partners broadly while remaining independent.
• Communication – concise, direct, and audience-appropriate; writes excellent docs and runbooks.
• Customer/Operator Empathy – designs for the people who actually use the workflow.
• Learning Agility & Curiosity – tracks emerging AI capabilities; adapts rapidly.
• Resilience – comfortable with imperfect data, pivots, and iteration.
• Ethical Judgment – thoughtful about data use, bias, and responsible deployment.
• Ownership – prioritizes impact over hierarchy; accountable for results.

Essential Functions

Working conditions are in a normal office environment. While performing the duties of this job, the employee is regularly required to walk; sit and stand; using the hands to handle, finger, or feel objects, tools, or controls. Occasionally, the employee must crouch or kneel. The employee must occasionally exert or lift up to 20 pounds. Successful performance requires good eyesight with or without corrective lenses. Requires long periods of time working at a computer and includes phone work. Some travel may be required for special company events (for example in Union City CA or Chicago).

Disclaimer

The above information on this description has been designed to indicate the general nature and level of work performed by employees within this classification and may be amended at any time at the sole discretion of the Employer. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.