Lead Forward Deployed Engineer, Microsoft AI & Data

Deloitte · San Francisco, CA · 2 days ago

HybridInformation Technology$189k–$373k/yrFull-time

About the role

Forward Deployed Engineers (FDE) at Deloitte help clients transform AI ambition into enterprise-scale impact by pairing leading-class engineering with pod-based delivery and vertical expertise.

Responsibilities

Serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production.
Set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team.
Translate engineering trade-offs into clear decisions for client leaders when needed.
Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements.
Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations, and overall delivery health.
Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls.
Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.
Review and contribute to production-quality code.
Guide architecture of data pipelines powering GenAI use cases.
Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices.
Operate within hybrid onshore/offshore teams.

Requirements

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
7+ years of experience in software engineering, data engineering, data science, or analytics engineering.
1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments.
1+ years of experience with Microsoft AI&Data including hands-on experience with Azure AI Foundry.
1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions.
1+ years of experience building reliable, maintainable, and well-documented code.
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.

Preferred Qualifications

Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking).
Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments.
Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation.
Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management.
Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures.
Familiarity with security, privacy, and compliance considerations.

Benefits

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $189,200 to $372,900.