Founding AI Lead - Forward Deployed Engineering

Founding AI Lead, Forward Deployed Engineering

About the Opportunity

A leading global alternative asset management firm, with more than $300 billion in assets under management and teams across private equity, impact, credit, real estate, and market solutions, is hiring a founding AI lead to help build a new Forward Deployed Engineering (FDE) team.

This is a builder-leader role. You'll set up the function from scratch: hiring the team, defining how it operates, and setting the technical bar. You'll also stay hands-on, writing code and shipping production-ready AI products inside the firm's highest-value workflows. You'll start with a small team of VP-level engineers and scale the capability as demand and impact grow.

You'll work directly with Partners, Managing Directors, and department heads to find the problems worth solving, shape ambiguous opportunities into real plans, and decide when a prototype is ready to become a product.

What You'll Do

• Build and lead the FDE function, starting with VP-level engineers. Hire, mentor, and retain strong engineers, and set the culture, standards, and talent model as the team grows.
• Manage team capacity, prioritization, and resource allocation to maximize business impact across the FDE portfolio.
• Define the operating model: how opportunities are identified, prioritized, scoped, evaluated, shipped, adopted, handed off, scaled, or retired.
• Build AI products, digital coworkers, and workflow solutions that solve meaningful business problems across the firm.
• Guide the team on when to use agentic workflows, multi-agent architectures, retrieval systems, automation, traditional software, process redesign, or simply recommend not building at all.
• Set technical standards for AI products, including architecture patterns, security, access controls, observability, documentation, support expectations, and production readiness.
• Establish firm-wide standards for AI evaluation, reliability, and release readiness, covering quality, safety, business effectiveness, regression testing, and model or workflow drift.
• Design governance and delivery patterns for human-in-the-loop and above-the-loop systems, including review, approval, escalation, monitoring, and intervention.
• Partner with Security, Compliance, Legal, Data, Infrastructure, and application teams so AI solutions respect information barriers, entitlement models, audit requirements, and secure development practices.
• Partner with senior stakeholders to set clear expectations on what AI systems can and cannot do.
• Create reusable patterns and architectures that can be applied across teams and use cases.
• Evaluate build, buy, and partner options, and recommend the right approach based on business value, risk, cost, and long-term maintainability.
• Manage the FDE portfolio budget, technology vendor relationships, platform investments, and related cost, risk, and utilization decisions.
• Lead special projects that support the evolution of the FDE function and the broader Engineering organization.

What We're Looking For

• 10+ years of experience in software engineering or AI engineering and experience leading teams and delivering complex enterprise solutions.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field (equivalent practical experience considered).
• A proven record of building teams, shipping production software, and delivering measurable business outcomes.
• Experience managing or leading senior engineers and setting technical standards, raising the bar without creating unnecessary bureaucracy.
• Experience building, scaling, or transforming an engineering function, platform, or capability, including the standards, talent model, operating cadence, and handoff patterns needed to grow beyond a first team.
• Hands-on AI application development, including model integration, context and retrieval design, evaluation frameworks, agentic workflows, workflow orchestration, human-in-the-loop processes, and production deployment.
• Experience building AI solutions on unstructured data such as investment memos, CIMs, credit agreements, LP communications, contracts, financial statements, and presentations.
• Experience designing, testing, and deploying AI systems with appropriate security and control measures, including prompt injection resistance, jailbreak testing, output guardrails, sensitive information protection, and model risk mitigation.
• Strong production engineering discipline: code review, testing, version control, CI/CD, secure development, documentation, and operational ownership.
• A product mindset: you identify the underlying problem, weigh alternative approaches, and deliver solutions people actually adopt.
• The ability to earn trust quickly with senior stakeholders, communicate trade-offs clearly, and turn ambiguous business needs into an executable technical plan.
• An enterprise-grade approach to engineering, where security, data access, auditability, compliance, and supportability are part of the design.
• Financial services fluency, with interest in or experience with investment, fund operations, or financial services workflows.

Technology

The team is technology agnostic and picks the right tool for each problem. You'll need credibility in modern AI application development and enterprise-grade software delivery. The team works with a range of technologies, including:

• Python, TypeScript, JavaScript, Java, .NET, or similar languages
• OpenAI, Anthropic, Gemini, Azure AI, Microsoft Copilot, and Copilot Studio
• Agentic and multi-agent architectures, tool calling, orchestration frameworks, and RAG
• Evaluation, observability, and model monitoring frameworks
• APIs, integrations, workflow automation, and distributed systems
• Azure, AWS, Google Cloud, and cloud-native architectures
• Databricks, SQL Server, vector databases, and modern data platforms
• CI/CD, test automation, and secure development practices

Why Join?

• Founding role: You'll build the function, its standards, and its culture from the ground up, with real input on how AI gets built and deployed across the firm.
• High-value problems: Your work will sit inside core investment and fund workflows, with direct exposure to senior investment professionals and operating leaders.
• Ownership: You decide what gets built, what gets bought, and what gets left alone, and you own the path from prototype to production.
• Real constraints, real impact: Information barriers, entitlements, and audit requirements are part of the job, so what you ship has to work in a regulated environment and get used.
• Scale potential: You'll start with a small team of senior engineers and have the chance to grow the function as demand and impact increase.
• Broad technical latitude: The team is technology agnostic, so you'll work across multiple model providers, cloud platforms, and modern data tooling.