AI & Data - Forward Deployed AI Engineer, Senior Manager

EY; Dublin; Hybrid; EUR 150,000 - 190,000; Full time

Benefits offered by this job

Hybrid working

Gym memberships

EY Tech MBA

Travel pass

Wellness rooms

Job summary

EY seeks a Senior Manager in AI & Data to lead client‑embedded AI initiatives, translating business needs into enterprise AI solutions from concept to production. You will drive architecture, data pipelines, and evaluation frameworks while aligning with client goals and enterprise security requirements.

The role emphasizes leadership, cross‑functional collaboration, and hands‑on experience with advanced ML systems, LLMs, and modern AI tooling in a consultancy setting.

Qualifications

• 7+ years of AI/ML engineering experience at Senior Manager level.
• Deep mastery across NLP/transformers, generative models (GANs/VAEs), reinforcement learning, classical ML and statistical modelling.
• Advanced LLM/RAG engineering: prompt pipelines, embeddings, vector stores (FAISS/Milvus/Pinecone).
• LLMOps/MLOps: automated testing, drift monitoring, CI/CD for ML, telemetry, lineage and governance.
• 7+ years of experience with cloud platforms (Azure preferred, GCP or AWS) and modern data infrastructure.
• Experience with containerisation and CI/CD pipelines.
• Proven ability to work with clients in a technical consulting or solutions engineering role.

Responsibilities

• Turn ambiguous business problems into AI solutions by partnering with clients to understand workflows and metrics.
• Translate business challenges into AI use cases (prediction, automation, retrieval, agent workflows).
• Define MVP scope, data requirements and evaluation criteria with stakeholders.
• Build fast prototypes using LLMs, RAG pipelines, fine‑tuning, agents, and ML models.
• Design and implement AI architectures including data ingestion, feature pipelines, embeddings, and model tuning.
• Integrate AI components with client systems (APIs, data warehouses, SaaS) and optimize latency and cost.
• Deploy solutions into client infrastructure (cloud/hybrid/on‑prem) with security and governance in mind.
• Set up monitoring for model performance, drift, and failures; manage risk and reliability.
• Provide technical training and knowledge transfer to client teams.
• Capture reusable patterns and contribute to internal playbooks and references.
• Support pre‑sales with technical credibility and demos.
• Stay current on AI tooling and capabilities.

Skills

AI/ML engineering

NLP/Transformers

Generative models

Reinforcement learning

ML modeling

Problem solving

Strong communication

Tools

LangChain

LangGraph

Llama Index

FastAPI

Job description

At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help build a better working world.

Business Area

AI & Data – Forward Deployed AI Engineer, Senior Manager

Contract Type

Full‑time – Permanent

Overview

As part of our AI & Data team, this role is pivotal in enabling our clients to derive significant value from AI. You will be a client‑embedded technical leader responsible for translating AI ambition into trusted, enterprise‑grade solutions and carrying them from concept through production while supporting continuous evolution of AI capabilities.

Key Responsibilities

• Turn ambiguous business problems into concrete AI solutions by partnering with clients to understand workflows, constraints, success metrics, and incentives.
• Translate business challenges into well‑scoped AI use cases (prediction, automation, retrieval, agent workflows).
• Define MVP scope, data requirements, and evaluation criteria jointly with stakeholders.
• Build fast prototypes using LLMs, RAG pipelines, fine‑tuning, agents, and traditional ML models where appropriate.
• Design and implement AI architectures, including data ingestion, feature pipelines, embeddings, vector stores, model selection, tuning and evaluation. Design prompts, guardrails and system instructions.
• Integrate AI components with existing client systems (APIs, data warehouses, SaaS platforms) and optimize for latency, cost, reliability and scalability.
• Deploy solutions into client infrastructure (cloud, hybrid, on‑prem) while navigating security, compliance, data residency and legacy constraints.
• Set up monitoring for model performance and drift, prompt failures, hallucinations and regressions.
• Provide technical training and knowledge transfer to client teams.
• Capture reusable patterns, architectures and accelerators, contribute to internal playbooks and reference implementations.
• Support pre‑sales with technical credibility and demos.
• Stay current on fast‑moving AI tooling and model capabilities.

Qualifications

• 7+ years of AI/ML engineering experience (Senior Manager level) with strong fundamentals in data structures, algorithms, and system design.
• Deep applied AI/ML mastery across NLP/transformers, generative models (GANs/VAEs), reinforcement learning, classical ML and statistical modelling.
• Advanced LLM/RAG engineering: prompt pipelines, embeddings, vector stores (FAISS/Milvus/Pinecone), hybrid retrieval, grounding, hallucination mitigation and evaluation frameworks.
• LLMOps/MLOps knowledge: automated testing, drift monitoring, safety/guardrails, CI/CD for ML, telemetry, lineage and governance.
• 7+ years of experience with cloud platforms (Azure preferred, GCP or AWS) and modern data infrastructure.
• Experience with containerisation and CI/CD pipelines.
• Proven ability to work with clients in a technical consulting, solutions engineering, or product engineering role.
• Strong problem‑solving skills and ability to navigate ambiguous requirements and iterate rapidly.
• Excellent communication skills for explaining complex technical concepts to technical and non‑technical audiences.
• Background in machine learning and hands‑on experience training or fine‑tuning models.
• Head‑count experience and significant management experience.
• Familiarity with enterprise security, compliance and governance requirements (SOC 2, GDPR, HIPAA).
• Demonstrated ability to lead multi‑disciplinary teams through complex delivery cycles.

Preferred Skills

• Experience building and deploying AI agents or autonomous systems in production.
• Experience with modern Python AI stack (LangChain, LangGraph, Llama Index, FastAPI).
• Previous work in a forward‑deployed, field engineering or technical account management role.
• Domain expertise in finance, healthcare, government, or manufacturing.

Benefits and Working Conditions

• Competitive remuneration package and comprehensive Total Rewards, including flexible working, career development, holidays, health and well‑being, insurance, savings and discounts.
• Hybrid working, work‑mobile, gym memberships, paid MBA (EY TECH MBA), travel pass and wellness rooms.
• Recognition awards, cash incentive for referrals, supportive coaching, and progressive learning opportunities.

EY is committed to being an inclusive employer and welcomes applications from people of all backgrounds. Reasonable accommodations are offered at every stage of the recruitment process.