About the Role
HEAD OF AI DEPLOYMENTS/OUTCOME ENGINEERING needed at one of our Agentic AI Investment Technology STARTUP clients!!! Hybrid 3 days a week in office in NYC only. Base $200k - $250k plus bonus/commission and EQUITY. Looking for someone ideally with experience running AI teams at top consulting firms, private equity firms, investment banks or asset managers.
Our client develops autonomous AI agents that eliminate the repetitive, manual work slowing down financial institutions. Their technology supports credit, investment, ESG, and compliance workflows for leading asset managers, PE firms and investment banks.
Outcome Engineers (OEs) work directly with investment institutions, translate complex analyst workflows into structured AI logic, and deliver production-grade automation that drives measurable outcomes for clients.
The Head of Outcome Engineering is responsible for building, leading, and scaling this function. This is a foundational leadership role — part product strategist, part technical architect, part client leader. You will hire and mentor a world-class OE team, codify methodologies, and ensure that every deployment deepens our product moat and expands our commercial impact.
This role is ideal for someone who has operated at the intersection of financial analysis, AI/LLM workflows, product development, and enterprise delivery, and who is now ready to build a category-defining function from the ground up.
You will report to the CEO, with close alignment to Product, Engineering, and Sales.
What You Will Lead
A. Build and Scale the Outcome Engineering Function
- Hire the first cohort of Senior OEs and establish the core operating model of the team.
- Design and run the OE Academy: a structured program to train high-potential talent from finance or AI backgrounds into workflow engineers.
- Define the OE career ladder, operating principles, technical standards, and delivery playbooks.
B. Deliver World-Class Workflow Automation for Clients
- You will ensure that AI agents deliver correct, reliable outputs across credit, investment, monitoring, and ESG workflows.
You will guide OEs as they:
- Shadow analysts and map messy workflows
- Design multi-step agent logic (prompts, chaining, evals, error paths)
- Ship production-grade workflows in weeks, not months
- Ensure every workflow includes evals, audit trails, and logic transparency
C. Ensure Repeatability and Productization
- Build the mechanisms that turn client-specific workflows into reusable primitives, components, and SKUs in the core platform.
- Establish standards for what becomes “product,” what stays “configuration,” and what is never built as bespoke.
- Drive a predictable feedback loop with Product & Engineering to accelerate roadmap development.
- Build central libraries for reusable modules (e.g., covenant analysis, EBITDA adjustments, risk signals)
- Ensure OEs aren’t rebuilding the wheel for each client
D. Partner with Sales to Drive Expansion
The OE function is a core revenue engine.
- Co-own account expansion outcomes: identifying adjacent teams, new workflows, and new regions where agents can deliver value.
- Reduce time-to-value for new deployments and accelerate commercial adoption.
- Build trusted relationships with senior client stakeholders (MDs, Heads of Credit, CIOs, COOs).
- Drive OE-touched accounts toward 140–150%+ NRR
E. Build an Organization That Scales Efficiently
- Maintain strong delivery economics, balancing speed, quality, and reusability.
- Ensure the OE function grows in leverage, not one-to-one with revenue.
- Create capacity planning, utilization models, and repeatable delivery frameworks that support high-growth enterprise scale.
- Knowing when to say “no” or re-scope overpromised work
Ideal Background & Experience:
- 10+ years in a hybrid role across finance, AI, product, or forward-deployed/solutions teams.
The ideal candidate will have experience in at least two of the following domains, and exposure to all three:
1. Financial Workflows
- Prior experience in private credit, PE, asset management, investment research, portfolio monitoring, or credit analytics.
- Ability to understand and validate logic in credit memos, IC decks, monitoring packs, risk frameworks, KPIs, and underwriting models.
2. AI / Technical Workflow Engineering
- Experience designing or supervising multi-step LLM workflows, prompt chains, eval design, error-handling strategies, and structured output pipelines.
- Comfortable guiding non-engineers to build high-quality prototypes in Python, SQL, or low-code platforms.
3. Client-Facing Enterprise Delivery
- Led teams delivering complex, cross-functional deployments at financial institutions or highly regulated enterprises.
- Skilled in stakeholder management, discovery, requirements shaping, success metrics, and escalations.
Leadership Qualities We’re Looking For:
Technical Depth + Domain Authority
- Able to mentor OEs on financial logic, AI workflow design, and structured evaluation.
Outcome Orientation
- Balances “client value tomorrow” with “platform scalability next quarter.”
-Builder Mentality
- Comfortable being a player-coach early, then scaling into organizational design and leadership.
Commercial Instinct
- Naturally sees expansion pathways and understands the economic drivers of high-NRR enterprise SaaS.
Operational Excellence
- Strong instincts for process, repeatability, and margin discipline — but only when the time is right.
Executive Presence
- Credible with Heads of Credit, Partners, CIOs, and CTOs; trusted as a thought partner.
Why This Role Matters
This team ensures:
- Every deployment succeeds
- Every workflow becomes a product asset
- Every client becomes a multi-workflow franchise
- Every win expands our moat
The Head of Outcome Engineering is shaping how automation will transform the future of financial analysis for the industry’s most sophisticated institutions.