Forward-Deployed AI Engineering Lead

Fdetimes; New York (NY); Sur place; USD 136 000 - 253 000; Plein temps

Avantages offerts par ce poste

Hybrid Work Model

Two company-wide Mental Health Days

Headspace app access

401k with company match

Flexible vacation

Résumé du poste

Thomson Reuters is seeking a seasoned engineering leader to head a team delivering production AI solutions for public accounting firms and corporate tax departments. You will recruit and develop senior engineers, shape teams per client engagement, and oversee rapid prototypes to multi-month AI implementations.

You will provide technical judgment on architecture, cost, and risk, while ensuring quality, governance and client satisfaction across engagements in a regulated domain.

Qualifications

• 10+ years of experience in software engineering or technical consulting, including 5+ years managing engineering teams, with demonstrated success hiring, developing and retaining senior engineers.
• Ownership of client-facing engineering delivery in consulting, professional services or a comparable environment, including staffing, resource allocation, utilization and capacity forecasting.
• Experience leading teams that shipped LLM-powered applications into production, with the ability to explain architecture, implementation decisions, operating costs and technical tradeoffs.
• Hands-on experience with modern AI engineering practices, including RAG, agentic workflows, function calling or Model Context Protocol (MCP), evaluation frameworks and observability.
• Daily use of AI coding tools, such as Claude Code, Cursor or GitHub Copilot, and experience establishing team workflows around them.
• Ability to assess and address AI risks in regulated environments, including hallucinations, data leakage, prompt injection and audit-trail integrity.
• Demonstrated technical decision-making, people development, delivery prioritization and stakeholder communication, including managing expectations and resolving escalations with senior client executives and internal leaders.

Responsabilités

• Build, lead and develop a senior engineering team of engagement leads, AI engineers and integration engineers, owning hiring, coaching, performance management and career development.
• Own staffing, capacity planning and delivery forecasting across client engagements, matching skills and availability to demand, maintaining capacity for pre-sales prototypes and addressing resource gaps before they affect delivery.
• Provide technical leadership for production AI solutions, reviewing architecture, scope, estimates and operating costs across retrieval-augmented generation (RAG), AI agents, tool integrations and prompt and context engineering.
• Set standards for AI quality, evaluation and risk controls, including reference datasets, expert review, regression testing, accuracy thresholds and safeguards appropriate for regulated tax and audit work.
• Own delivery health and client outcomes across engagements, managing scope, risk, quality and client satisfaction while serving as the escalation point for clients and internal teams.
• Improve engineering effectiveness through AI-enabled development, embedding AI coding tools, automated testing, evaluation pipelines and reusable solutions into team workflows.
• Partner with business, product, consulting and platform leaders to align demand with capacity, resolve competing priorities, support transitions into ongoing support and report on utilization, throughput and forecast accuracy.

Connaissances

Experience leading teams that shipped

Hiring and developing senior engineers

Staffing and capacity forecasting

AI engineering practices (RAG, MCP, MC

AI tooling (Claude Code, Cursor, GitHu

AI risk in regulated environments

Stakeholder communication with execs

Outils

LLM-powered production systems

Description du poste

Thomson Reuters is seeking a seasoned engineering leader to head a team delivering production AI solutions for public accounting firms and corporate tax departments. You will recruit and develop senior engineers, shape teams per client engagement, and oversee rapid prototypes to multi-month AI implementations.

You will provide technical judgment on architecture, cost, and risk, while ensuring quality, governance and client satisfaction across engagements in a regulated domain.