Location
Dublin 2
Other locations: Primary Location Only
Contract Type
Full-Time – Permanent
Business Area
AI & Data - Forward Deployed AI Engineer, Senior Manager
Team and Opportunity
As part of our AI & Data team, this role is pivotal in enabling our clients to derive significant value from AI. Through collaboration and domain expertise, our team embeds innovative AI & Data solutions into existing business areas, transforming data into strategic assets. We are looking for a Forward Deployed AI Engineer who is passionate about leveraging AI & data to solve complex problems and drive business outcomes.
Role Overview
As a Forward Deployed AI Engineer at EY, you will be a client-embedded technical leader responsible for translating AI ambition into trusted, enterprise-grade solutions. You will work closely with EY Partners, engagement teams, and senior client stakeholders to design, build, and deploy AI systems that operate effectively within complex, regulated, and large-scale environments. This role blends deep hands‑on engineering, consulting judgment, and client‑facing delivery ownership. You will carry solutions from concept through production and enable clients to sustainably operate and evolve their AI capabilities.
Your 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 (e.g., 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, traditional ML models where appropriate.
- Design and implement AI architectures, including data ingestion, feature pipelines, embeddings, vector stores, model selection, tuning, and evaluation. Prompt design, guardrails, and system instructions.
- Integrate AI components with existing client systems (APIs, data warehouses, SaaS platforms). Optimize for latency, cost, reliability, and scalability.
- Deploy solutions into client infrastructure (cloud, hybrid, on‑prem), navigating real‑world constraints such as security, compliance, data residency, legacy systems.
- 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.
- Share lessons learned across engagements.
- 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 with strong fundamentals in data structures, algorithms, and system design with Python in production environments.
- Deep applied AI/ML mastery: 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: 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 containerization and CI/CD pipelines.
- Proven ability to work with clients in a technical consulting, solutions engineering, or product engineering role.
- Strong problem‑solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions.
- Excellent communication skills with the ability to explain complex technical concepts to both technical and non‑technical audiences.
- Background in machine learning, with hands‑on experience training or fine‑tuning models.
- Relevant experience in consulting or industry with significant management experience.
- Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA).
- Demonstrated ability to lead multi‑disciplinary teams (engineering, data science, architecture, product, design) through complex delivery cycles.
Preferred Skills
- Experience building and deploying AI agents or autonomous systems in production.
- Experience using modern Python AI stack (e.g., LangChain, LangGraph, LlamaIndex, FastAPI).
- Previous work in a forward deployed, field engineering, or technical account management role.
- Domain expertise in verticals like finance, healthcare, government, or manufacturing.
Benefits
- Competitive remuneration package.
- Support and coaching from engaging colleagues.
- Opportunities to develop new skills and progress your career.
- Freedom and flexibility to handle your role in a way that’s right for you.
Employee Benefits
- Pension.
- Maternity & Paternity leave.
- Discounted health insurance.
- Bike to work Scheme.
- Web Doctor – free unlimited online GP consultations for you and your family.
- Recognition Awards.
- The purchase of additional annual leave.
- Cash incentives for referrals.
- Hybrid Working.
- Free Gym membership.
- TECH MBA paid by EY.
- Travel Pass.
- Wellness rooms available in some offices.
Workplace Flexibility
EY is committed to providing flexible working arrangements. While client‑facing professionals may be required to travel regularly and be based at client sites, flexible working options aim to support a good work‑life balance.
EEO Statement
As an equal opportunities employer, we welcome applications from people of all backgrounds. Reasonable accommodations are offered at every stage of our recruitment process.