AFE Cell Lead - AI Advanced Forward Engineering - Manager

About the role

We are seeking a hands-on Lead Forward Deployed Engineer (FDE) to own the end-to-end delivery of AI-native systems into a single client engagement in highly regulated industries such as tax, finance, and risk.

Responsibilities

• Own end-to-end outcome delivery for the cell, including scoping, tradeoffs, technical direction, and production readiness, taking accountability for the business outcome, not just the code.
• Embed directly with the client to define the real problem and translate ambiguous business needs into an executable technical solution under regulatory and environmental constraints.
• Serve as the primary technical interface and trusted advisor to client stakeholders, managing expectations, communicating tradeoffs, and sustaining the trust that drives adoption.
• Stay hands-on, personally designing and building critical parts of the solution, and diving deep into the client’s systems, data, and codebase when the engagement requires it.
• Deploy, adapt, and stabilize solutions in the client environment using supported templates and profiles, owning release readiness and runtime accountability for what the cell ships.
• Direct the work of the cell’s Implementation Engineer and Data Engineer, ensuring integrations, orchestration, and data readiness come together into a coherent, production-grade outcome.
• Ensure every deployment meets safety, integrity, and cost constraints, partnering with control authorities and the Distinguished AFE on safe-to-ship decisions for regulated environments.

Requirements

• Strong outcome ownership: able to take accountability for delivering a business result under real-world constraints, not just completing technical tasks.
• Excellent client presence: credible with both technical teams and senior business stakeholders, and able to build trust quickly in high-stakes settings.
• Genuinely hands-on: comfortable diving deep into code, data, and messy legacy systems while still leading the engagement.
• Strong technical judgment in complex, distributed, AI-enabled systems, with the ability to make sound decisions autonomously.
• Effective at communicating complex technical tradeoffs clearly and with evidence to varied audiences (technical / executive).
• Comfortable operating with autonomy in small, senior teams, often solo at a client site.
• Pragmatic mindset: balance ideal design against regulatory, organizational, and environmental realities.
• 8+ years delivering complex enterprise systems, ideally in regulated or client-facing contexts.
• Hands-on engineering depth across integration-heavy architectures, cloud platforms, and distributed systems.
• Experience with modern AI-enabled application stacks (e.g., agentic systems, orchestration frameworks, LLM-backed services).
• Proven ability to operate in forward-deployed, customer-facing, or solutions-architecture roles, owning outcomes end to end.
• Proven ability to lead a small technical team while remaining an individual contributor.
• Strong stakeholder-management skills, including managing client expectations under pressure.
• Solid understanding of software delivery lifecycle, quality gates, and production readiness in enterprise settings.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related technical field.
• Experience deploying solutions into client environments (cloud, on-prem, hybrid, or air-gapped).
• Experience working within AI governance, security, or cost controls in production environments.
• Exposure to regulated delivery contexts (e.g., financial services, tax, healthcare, risk platforms).

Skills

• Strong outcome ownership: able to take accountability for delivering a business result under real-world constraints, not just completing technical tasks.
• Excellent client presence: credible with both technical teams and senior business stakeholders, and able to build trust quickly in high-stakes settings.
• Genuinely hands-on: comfortable diving deep into code, data, and messy legacy systems while still leading the engagement.
• Strong technical judgment in complex, distributed, AI-enabled systems, with the ability to make sound decisions autonomously.
• Effective at communicating complex technical tradeoffs clearly and with evidence to varied audiences (technical / executive).
• Comfortable operating with autonomy in small, senior teams, often solo at a client site.
• Pragmatic mindset: balance ideal design against regulatory, organizational, and environmental realities.
• Hands-on engineering depth across integration-heavy architectures, cloud platforms, and distributed systems.
• Experience with modern AI-enabled application stacks (e.g., agentic systems, orchestration frameworks, LLM-backed services).
• Proven ability to operate in forward-deployed, customer-facing, or solutions-architecture roles, owning outcomes end to end.
• Proven ability to lead a small technical team while remaining an individual contributor.
• Strong stakeholder-management skills, including managing client expectations under pressure.
• Solid understanding of software delivery lifecycle, quality gates, and production readiness in enterprise settings.

Benefits

• Comprehensive compensation and benefits package.
• Flexible vacation policy.
• Support for personal/family care leave.

Pay

The base salary range for this job in all geographic locations in the US is $125,500 to $230,200. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $150,700 to $261,600. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.

Schedule

Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.