Tech S and T-AI -Architect-ISR-SeniorManager-GDSF02
Ernst and Young1 day ago
Noida, IndiaStaff+
Responsibilities
- Architect and deliver AI, ML, LLM, and agentic solutions embedded in infrastructure operations.
- Design and build multi-step, tool-using agents for ticketing, monitoring, remediation, and provisioning.
- Evaluate, fine-tune, and integrate open-source and commercial LLMs into enterprise infrastructure tooling.
- Build RAG pipelines, vector databases, and knowledge-grounding systems using infrastructure documentation, runbooks, and CMDB data.
- Write production-grade Python, Bash, and PowerShell code and integrate AI solutions with cloud, ITSM, observability, and CI/CD platforms.
- Define AI governance guardrails covering data privacy, model security, hallucination control, and cost/token management.
- Identify high-value AI use cases, develop the roadmap, and own the proof-of-concept through production lifecycle.
- Establish MLOps and LLMOps practices, mentor infrastructure engineers, and lead the infrastructure AI Center of Excellence.
- Present AI strategy and business cases to infrastructure leadership and other stakeholders.
Requirements
- 16–18 years of experience in infrastructure/cloud engineering or architecture, with the last 5–6 years focused on applied AI, ML, or LLM work.
- Strong hands-on Python development, API integration, and SDK experience, including OpenAI, Anthropic, LangChain, and LlamaIndex.
- Understanding of LLM prompting, fine-tuning, embeddings, RAG, context windows, and token/cost management.
- Practical experience building agentic AI systems with LangGraph, AutoGen, CrewAI, or custom orchestration and tool/function calling.
- Experience with vector databases such as Pinecone, Weaviate, FAISS, and Azure AI Search.
- Deep infrastructure experience spanning cloud architecture, networking, virtualization, ITSM, monitoring/observability, automation, Ansible, and Terraform.
- Experience with MLOps/LLMOps, including model deployment, monitoring, versioning, and cost governance.
- Strong architecture and solutioning skills with the ability to design and defend end-to-end systems.
- Preferred AWS, Azure, or GCP AI/Solutions Architect certifications.
- Exposure to enterprise AI governance and responsible AI frameworks is preferred.
- Experience presenting AI strategy and business cases to CXO or senior leadership is preferred.
- Big Four, GDS, or large-enterprise infrastructure experience is preferred.
- Open-source contributions or published proofs of concept in AI or agentic systems are preferred.
- Strong stakeholder management and communication skills across infrastructure, data science, and business teams.
Tech Stack
Categories
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.