EY - GDS Consulting - AIA - AI Engineer- Senior
EY
AI Engineer-GenAI, Agentic AI, RAG and Enterprise AI Engineering
Career Family: AIA - AI / GenAI / Agentic AI
The opportunity
We are seeking an AI Engineer with strong hands-on experience building enterprise-grade AI/ML, Generative AI, RAG, conversational AI and Agentic AI solutions. The engineer will contribute across design, development, testing, deployment, observability and production support, working closely with architects, data scientists, application engineers, UX teams, security teams and business stakeholders.
The successful candidate must be able to explain at least one or two enterprise, pre-production or production AI implementations, including the business use case, individual contribution, technical approach, controls and outcomes. Certifications, personal projects and demonstrations alone are not sufficient.
Your Key Responsibilities
- Design, develop, test and support AI/ML, GenAI, RAG, conversational AI, copilot and AI-agent solutions aligned with business and architecture requirements.
- Build document ingestion, parsing, chunking, embedding, indexing, retrieval, reranking, grounding and prompt-orchestration pipelines.
- Develop tool-enabled agents and multi-agent workflows using function calling, memory, enterprise APIs and human-in-the-loop patterns.
- Build scalable backend services and integrations using Python, FastAPI, REST APIs, microservices, asynchronous processing and event-driven patterns.
- Develop or integrate modern user experiences for chatbots, copilots and agents using React, TypeScript or equivalent frameworks when required.
- Implement real-time AI interactions using WebSockets, Server-Sent Events or token streaming, including safe rendering and resilient error handling.
- Integrate AI solutions with enterprise applications, workflow platforms, databases, vector stores, search services and cloud data platforms.
- Implement evaluation and quality checks for retrieval, groundedness, accuracy, hallucination risk, prompt performance, tool execution, latency and cost.
- Apply Responsible AI, PII protection, access controls, data privacy, secure coding, prompt-injection mitigation, content safety and auditability controls.
- Containerize and deploy services, contribute to CI/CD pipelines, automated tests, monitoring, logging, release management and production support.
- Troubleshoot issues across data pipelines, models, prompts, agent workflows, APIs, vector stores, streaming services and user interfaces.
- Prepare technical designs, implementation notes, test evidence, runbooks, solution walkthroughs and delivery updates.
- Contribute reusable components, SDKs, accelerators and engineering standards; guide junior team members where required.
Professional experience
- 4-8 years of overall professional experience in AI/ML, data engineering, cloud engineering, software development or related fields.
- Hands-on experience contributing to enterprise or client-facing AI/ML, GenAI, copilot, conversational AI, Agentic AI or RAG solutions.
- Practical experience taking solution components through development, testing, deployment and operational support.
- Ability to collaborate effectively with architects, managers, product owners, engineers and business stakeholders.
- Strong proficiency in Python and working knowledge of SQL, data structures, algorithms, software engineering and object-oriented design.
- Strong understanding of LLMs, prompt engineering, RAG, embeddings, semantic and hybrid search, vector databases, conversational AI and AI agents.
- Hands-on experience with one or more frameworks such as LangChain, LangGraph, AutoGen, CrewAI, Microsoft Agent Framework or Google Agent SDK; familiarity with MCP is preferred.
- Experience developing APIs and scalable services using FastAPI, REST, JSON, microservices, asynchronous workflows and event-driven architecture.
- Experience with at least one cloud AI platform such as Azure AI Foundry and Azure OpenAI, AWS Bedrock, or GCP Vertex AI and Gemini.
- Experience with vector stores and search platforms; exposure to relational databases, MongoDB, Redis, ClickHouse or equivalent data technologies is beneficial.
- Understanding of machine learning, NLP, model integration, model evaluation, data preparation and feature engineering.
- Working knowledge of Docker, Kubernetes or OpenShift, Git, GitHub Actions or GitLab CI, automated testing, CI/CD, MLOps and LLMOps.
- Experience implementing logging, monitoring, tracing, AI observability, performance optimization and production support.
- Understanding of Responsible AI, security, privacy, PII protection, guardrails, hallucination checks, accessibility and safe display of model output.
- Working knowledge of React, TypeScript and Next.js, with experience building or integrating chat, copilot or agent interfaces preferred.
- Exposure to reusable UI components or SDKs, typed API clients, state management, design systems and accessible user experiences.
- Experience with WebSockets, Server-Sent Events or token-level LLM streaming is preferred.
- Strong analytical and problem-solving skills with the ability to translate requirements into practical engineering tasks.
- Good written and verbal communication, documentation, collaboration and stakeholder-management skills.
- Commitment to engineering quality, maintainable code, automated testing, continuous learning and innovation.
- Bachelor's or master's degree in Computer Science, Data Science, Artificial Intelligence, Information Technology, Engineering or a related discipline.
- Relevant certifications in Microsoft Azure, AWS, Google Cloud, Databricks, AI/ML or Generative AI are preferred.
- Be at the forefront of AI-driven innovation across multiple client sectors.
- Work with global clients to deliver measurable business impact.
- Collaborate with AI experts, analytics leaders and industry specialists in a highly entrepreneurial environment.
EY Global Delivery Services (GDS) is a dynamic and truly global delivery network. We work across six locations - Argentina, China, India, the Philippines, Poland and the UK - and with teams from all EY service lines, geographies and sectors, playing a vital role in the delivery of the EY growth strategy.
- Continuous learning: You will develop the mindset and skills to navigate whatever comes next.
- Success as defined by you: We provide the tools and flexibility so you can make a meaningful impact, your way.
- Transformative leadership: We provide insights, coaching and confidence to help you become the leader the world needs.
- Diverse and inclusive culture: You will be empowered to use your voice and help others find theirs.
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.