Head of Frontier Technologies

Tract Capital Management

Denver (CO)

Hybrid

USD 150,000 - 200,000

Full time

7 days ago

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Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

401K program

Paid holidays

Unlimited PTO

Job summary

Tract Capital Management is seeking a seasoned technology leader to drive AI/ML strategy across its portfolio. You will partner with portfolio CEOs and engineering teams to design, build, and operationalize AI initiatives, balancing quick wins with long-term platform bets.

You will oversee governance, vendor management, and integrations with enterprise systems, delivering measurable business outcomes across real estate, data centers, and construction domains.

Qualifications

10+ years in technology leadership with AI/ML focus at scale.
Proven track record shipping production AI/ML systems across portfolios.
Hands-on depth with LLMs and data platforms; integrates with ERPs.

Responsibilities

Define AI/ML strategy and roadmap across portfolio companies.
Lead or embed with delivery teams to ship AI/ML initiatives.
Establish reference architectures and data governance.
Oversee integrations with enterprise systems (e.g., NetSuite, Coupa).
Measure impact via KPIs: cycle time, cost avoidance, revenue impact.
Engage portfolio CEOs/COOs as trusted technology partner.

Skills

Strategic AI/ML leadership

Cross-functional leadership

Portfolio company engagement

Vendor management

Education

10+ years technology leadership

Tools

LLMs

Vector databases

NetSuite integration

Coupa integration

Job description

Tract Capital Management ("TCM") is a privately held investment management firm actively managing approximately $6.3 billion in AUM across three investment vehicles — Tract (LandCo) I, LP, Tract II, LP, and Fleet Data Centers I, LP — with 250+ employees across its businesses. TCM's wholly owned subsidiary, Fleet DC Services, LLC, develops and operates build‑to‑suit hyperscale data center campuses for the world's largest cloud and AI infrastructure customers. TCM is expanding internationally, with Tract II targeting European markets alongside its US portfolio.

Position Overview

This is not a pure strategy or advisory seat. The successful candidate in this role sets direction, then rolls up their sleeves — partnering with portfolio company leadership, engineering teams, and vendors to design, build, and operationalize solutions. Success is measured in deployed capability and business outcomes, not presentation decks.

Job Responsibilities

Strategy & Roadmap

Define the firm's point of view on AI/ML and emerging technology adoption across a diverse portfolio (data center operations, land/real estate strategy, construction, legal ops, EHS, CRM/quote-to-cash, and adjacent domains).
Build a prioritized, portfolio-wide AI/ML Strategy and roadmap that balances quick wins against multi-year platform bets.
Evaluate build‑vs‑buy‑vs‑partner decisions for AI/ML capabilities, including LLM‑based systems, data platforms, and vertical SaaS with embedded AI.
Track the frontier: new models, agent architectures, and tooling — translate what's real and applicable versus hype, and update the roadmap accordingly.

Architecture & Technical Direction

Set reference architectures and standards for AI/ML systems used across portfolio companies (e.g., LLM‑centric applications with vector‑backed data stores, integration patterns with core systems of record such as NetSuite, Coupa, and industry‑specific platforms).
Establish data architecture principles — source‑of‑truth design, pipeline standards, and governance — that let AI initiatives scale across companies without re‑solving the same problems.
Define evaluation frameworks for new platforms (EHS systems, DCIM/monitoring tools, construction tech, legal spend management) with AI/ML capability as an explicit selection criterion.

Execution & Delivery

Personally lead (or embed with) delivery teams to design and ship priority AI/ML initiatives from concept through production.
Stand up or oversee integrations between AI systems and enterprise platforms already in use across the portfolio.
Own program management for cross‑portfolio technology initiatives: scoping, sequencing, resourcing, and risk management.
Define and track KPIs that tie technology execution to business outcomes (cycle time, cost avoidance, revenue impact, risk reduction).

Portfolio Company Engagement

Act as the trusted technology partner to portfolio company CEOs/COOs — translating firm‑wide strategy into a plan that fits each company's stage, resources, and risk tolerance.
Run technology and AI readiness assessments for new and existing portfolio companies, including as part of diligence for acquisitions.
Build internal capability at the portfolio company level so initiatives are sustainable without permanent central‑team dependency.

Governance, Risk & Vendor Management

Establish AI governance practices: data privacy, model risk, compliance (including any sector‑specific regulatory considerations), and responsible‑use policies.
Own the vendor landscape for AI/ML and adjacent platforms — evaluation, negotiation support, and lifecycle management.
Partner with legal/compliance on emerging regulatory and IP considerations tied to AI adoption.

Education & Experience

10+ years in technology leadership, with at least 3–5 years focused on AI/ML strategy and delivery (not just strategy) at scale.
A track record of shipping — not just architecting — production AI/ML systems, ideally across multiple business units or portfolio‑style environments (PE, holding company, multi‑BU enterprise).
Hands‑on technical depth: comfortable evaluating and directing work involving LLMs, retrieval‑augmented architectures, vector databases, and integration with enterprise systems of record.
Experience operating in asset‑heavy or operationally complex industries (real estate, construction, infrastructure, data centers, industrials) is a strong plus — you understand the gap between "AI demo" and "AI that survives contact with field operations."
Strong program and change‑management skills — you can drive adoption across teams that didn't ask for a new tool.
Comfort operating with a small central team and a large "influence without authority" surface area across autonomous portfolio companies.
Excellent communication — equally credible in front of a portfolio company's ops leadership and the firm's investment committee.

Technical / Functional Expertise

Hands‑on technical knowledge of large language models, retrieval‑augmented architectures, vector databases, and integrations with enterprise systems of record.
Experience defining reference architectures, data architecture standards, governance frameworks, and system integration patterns.
Ability to evaluate and direct the development of production AI and machine learning systems.
Strong program management and change‑management capabilities.
Experience evaluating, selecting, onboarding, and managing AI, machine learning, and enterprise technology vendors.
Knowledge of AI governance, data privacy, model risk, compliance, responsible‑use practices, and emerging regulatory and intellectual property considerations.

Industry Experience

Experience operating within asset‑heavy or operationally complex industries such as real estate, construction, infrastructure, data centers, or industrials is strongly preferred.
Experience deploying technology within field‑based or operational environments is preferred.
Experience supporting autonomous portfolio companies or multiple business units is strongly preferred.

Core Skills & Competencies

Strong execution‑oriented mindset with the ability to move initiatives from strategy through production deployment.
Ability to operate effectively with a small central team and influence stakeholders across autonomous portfolio companies without direct authority.
Strong leadership, strategic thinking, analytical problem‑solving, and decision‑making skills.
Excellent communication and stakeholder‑management skills, with the ability to engage credibly with operational leadership, executive teams, and investment committees.
Ability to drive adoption and organizational change across teams with different levels of technical readiness.
Strong ownership, autonomy, collaboration, and accountability for measurable business outcomes.

Success Looks Like (First 12 Months)

A ratified, portfolio‑wide AI/ML strategy and architecture standard.
At least 2–3 production deployments across different portfolio companies with measurable business impact.
A repeatable playbook for evaluating and onboarding new AI/ML tools and vendors.
Trusted‑advisor relationships established with leadership at each major portfolio company.

Location

Hybrid / Headquarters‑based with portfolio company site travel. Specific headquarters location to be confirmed.

Travel Requirement

Approximately four to six portfolio company site visits per year.

Expected Salary Range

$150,000 - 200,000 Base Salary + Discretionary Bonus

Tract Capital Employment

Tract Capital employees enjoy competitive compensation and comprehensive benefits, including 100% employer‑covered medical, dental, and vision insurance, a 401K program, standard paid holidays, and unlimited PTO.

Tract Capital is proud to be an Equal Opportunity Employer. Qualified applicants are considered for employment regardless of age, race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or veteran status. If you need assistance applying for any of our open positions, please contact us at info@tractcapital.com.

NOTE: This job description is not intended to be all‑inclusive. Employees may perform other related duties to meet the organization’s ongoing needs.

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