Forward-Deployed AI Engineer & Model Lead

EY

Minneapolis (MN)

Remote

USD 126,000 - 230,000

Full time

6 hours ago

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Benefits offered by this job

Medical and dental coverage

401(k) plans

Paid time off

Job summary

EY’s AI, Data & Engineering team is seeking a Forward Deployed Engineer Manager to work directly with clients, diagnosing business problems and delivering AI/ML, generative AI, and agentic solutions across cloud and on‑prem environments.

You will guide architecture, supervise delivery, and mentor teams, applying AI-native tools such as Claude, Codex, Cursor and GitHub to accelerate impact while ensuring responsible, high‑quality outcomes for complex client engagements.

Qualifications

Bachelor's degree required.
6-10 years of full-time experience in AI, Data Science, and/or Machine Learning.
2-4 years of experience directly managing technical teams.
Strong skills in Python.
Ability to lead, collaborate, and communicate effectively with diverse, hybrid and global teams.
Experience identifying, solutioning, designing, building, deploying, operating, and expanding high-impact, high-value production AI/ML solutions on a major cloud platform.
Proficient in foundation models, generative AI, and agentic AI frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)).
Experience with natural language processing and deep learning.
Extensive experience in AI-assisted and DevOps tools (Claude, Codex, Cursor, GitHub, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions.
Experience with MLOps, LLMOps, and AgentOps and ML workflows, including data ingestion, transformation, and evaluation.
Experience with model retraining and feedback loop methodologies.
Experience with model and solution evaluation, observability, monitoring, and reporting.
Understanding of data structures, data modelling, software engineering, and Responsible AI practices.
Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques.
Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements.
Skills in Technical Design Optimization
Strong relationship-building skills
Demonstrated client trust and value
Digital fluency and emotional agility
Commercial acumen and negotiation skills
Proven ability to lead teams and manage change.

Responsibilities

Leading client-embedded AI workstreams from opportunity identification and process diagnosis through solution design, production deployment, value measurement, and ongoing optimization.
Redesigning client processes for human-AI collaboration and continuously improving delivery by identifying innovative solutions through research, rapid prototyping, and analysis.
Managing lean, multidisciplinary teams to deliver complex AI engineering initiatives, while remaining close to architecture and build decisions and maintaining accountability for quality, responsible deployment, economics, and results.
Building trust with business and technology stakeholders, participating in daily client working sessions, and leading product and agile delivery from planning through execution and closure.
Demonstrating realized value, identifying adjacent use cases and opportunities for additional specialists or services, supporting solution demonstrations and proposals, and managing engagement economics.
Defining solution architecture and guiding hands‑on development of agentic workflows, orchestration logic, memory, retrieval, reusable components, APIs, MCP connectors, and agent‑to‑agent integrations.
Establishing evaluations, observability, control‑plane governance, access controls, and risk mitigations for secure and responsible operation of AI and agentic systems.
Using and coaching teams on AI-native development tools such as Claude, Codex, Cursor, and GitHub to increase delivery speed without compromising engineering quality.