EY - GDS Consulting - AIA - AI Platform Engineer- Senior

The opportunity

We are seeking a dynamic Senior consultant to join our AI & Data Consulting team, focused on building scalable, enterprise-grade GenAI and Agentic AI solutions. The ideal candidate will bring a strong combination of AI engineering, platform development, cloud-native architecture, and backend engineering expertise, along with the ability to collaborate across cross-functional teams to deliver secure, scalable, and high-performing AI applications.

You will work closely with data engineers, cloud architects, platform teams, security teams, product owners, and business stakeholders to design and implement LLM-powered platforms, agentic AI systems, Retrieval-Augmented Generation (RAG) solutions, and enterprise AI services that accelerate innovation and business transformation

Your key responsibilities

Technical Excellence:

 AI Engineering & Agentic AI Development

• Design and develop enterprise-grade GenAI applications leveraging LLM frameworks such as LangChain, LangGraph / AutoGen / Google Agent SDK, and Model Context Protocol (MCP).
• Build and deploy agentic AI architectures, including multi-agent workflows, tool/function calling, enterprise integrations, and autonomous decision-making systems.
• Develop and maintain Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking, embeddings generation, vector indexing, retrieval optimization, and response grounding.
• Implement semantic search and knowledge retrieval solutions using vector databases such as Azure AI Search, Pinecone, FAISS, Redis Vector, and pgvector.
• Design robust AI system architectures that ensure scalability, reliability, security, and performance.
• Contribute to AI evaluation, observability, monitoring, and performance optimization of LLM-powered applications.
• Stay current with emerging trends in GenAI, Agentic AI, multimodal AI, enterprise AI platforms, and AI engineering practices.

Backend & Platform Engineering

• Design and build scalable backend services using Python, FastAPI, REST APIs, microservices, and event-driven architectures.
• Develop reusable AI platform components, services, APIs, and integrations to accelerate enterprise AI adoption.
• Integrate AI solutions with enterprise systems, third-party applications, workflow platforms, and data services.
• Troubleshoot and optimize AI pipelines, APIs, vector stores, backend services, and cloud-native applications.
• Implement scalable deployment strategies using containerized and cloud-native architectures.

 Cloud, Infrastructure & DevOps

• Develop enterprise AI solutions using Azure OpenAI, Azure AI Services, and cloud-native services.
• Deploy and manage applications using Docker, Kubernetes, OpenShift, and container orchestration platforms.
• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, and modern DevOps tooling.
• Ensure production readiness through monitoring, observability, automated testing, release management, and operational excellence.
• Support deployment and lifecycle management across development, testing, staging, and production environments.

 AI Governance, Security & Responsible AI

• Implement enterprise controls for PII protection, data privacy, AI security, compliance, and responsible AI practices.
• Support AI governance initiatives through monitoring, auditability, access controls, and compliance frameworks.
• Contribute to AI observability practices, including monitoring model behavior, hallucination risks, accuracy, latency, and retrieval quality.
• Ensure adherence to enterprise architecture, security standards, and engineering best practices.

Team Collaboration & Delivery Excellence

• Collaborate with data engineers, cloud and platform teams, security teams, product owners, and business stakeholders to refine requirements and deliver scalable AI solutions.
• Participate in architecture reviews, code reviews, testing reviews, and technical design discussions.
• Drive engineering excellence through reusable components, documentation, automation, and quality standards.
• Support production operations including troubleshooting, performance tuning, root-cause analysis, and continuous improvement.

Skills and Attributes:

• Educational Background
• Bachelor’s degree in computer science, Information Technology, Engineering, or a related discipline.

Professional Experience

• 4+ years of professional software engineering experience with strong exposure to GenAI, LLMs, platform engineering, and backend development.
• Strong hands-on expertise in Python for AI application development and backend engineering.
• Experience building LLM-powered applications, RAG systems, agentic workflows, prompt engineering solutions, and enterprise AI integrations.
• Hands-on proficiency with LangChain, LangGraph, and exposure to AutoGen, Google Agent SDK, Model Context Protocol (MCP), or skills-based agent frameworks.
• Experience implementing vector search solutions using Azure AI Search, Pinecone, FAISS, Redis Vector, or pgvector.
• Strong understanding of embeddings, semantic search, chunking strategies, retrieval optimization, ranking, and context management.
• Experience developing scalable backend services using FastAPI, REST APIs, microservices, and event-driven architectures.
• Hands-on experience with Azure OpenAI and Azure AI Services.
• Knowledge of containerization technologies such as Docker, with exposure to Kubernetes and OpenShift.
• Experience implementing CI/CD pipelines using GitHub Actions, GitLab CI, or similar DevOps platforms.
• Strong understanding of SQL and NoSQL databases including MongoDB, Redis, ClickHouse, and scalable data architectures.
• Experience supporting enterprise AI systems through monitoring, observability, evaluation, and production operations.
• Understanding of AI governance, security, privacy, compliance, and responsible AI frameworks.
• Banking or financial services domain experience is preferred

Soft Skills

• Strong analytical and problem-solving capabilities.
• Excellent communication and stakeholder management skills.
• Ability to translate complex business requirements into scalable technical solutions.
• Strong collaboration skills across engineering, product, and business functions.
• Commitment to engineering excellence, continuous learning, and innovation

Preferred Certifications

GenAI and LLM focused, AI/ML, or data analytics certifications (Google, Microsoft, AWS, Coursera, etc.)

Why Join Us

• Be at the forefront of AI-driven innovation across multiple client sectors.
• Work with global clients to drive real business impact.
• Collaborate with a team of AI experts, analytics leaders, and industry specialists in a highly entrepreneurial environment.

What we offer

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. From accountants to coders to advisory consu