Tech S and T-AI Engineer-ISR-Manager-GDSF02
Ernst and Young1 day ago
Noida, IndiaStaff+
Responsibilities
- Architect and deliver AI/ML/LLM-based solutions embedded in infrastructure operations, including AIOps, self-healing systems, predictive capacity, and automated root-cause analysis.
- Design and build multi-step, tool-using agentic workflows 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 and Bash/PowerShell code and integrate AI solutions with cloud platforms, ITSM tools, observability stacks, and CI/CD pipelines.
- Define AI governance guardrails covering data privacy, model security, hallucination control, and cost/token management.
- Own the proof-of-concept, pilot, and production lifecycle for AI initiatives, including MLOps and LLMOps practices.
- Partner with infrastructure leadership on AI use cases and roadmaps, mentor infrastructure engineers, and lead the internal infrastructure AI Center of Excellence.
Requirements
- 10–12 years of infrastructure/cloud engineering or architecture experience, including the last 3–4 years focused on applied AI/ML/LLM work.
- Strong hands-on Python coding ability with API integration and SDK usage, 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, Ansible, and Terraform.
- Experience with MLOps/LLMOps, including model deployment, monitoring, versioning, and cost governance.
- Strong architecture, solutioning, stakeholder management, presentation, and strategic roadmap skills.
- Preferred qualifications include AWS, Azure, or GCP AI/Solutions Architect certifications; enterprise AI governance experience; CXO-level strategy presentation experience; Big Four, GDS, or large-enterprise infrastructure experience; and open-source contributions or published AI/agentic-system proofs of concept.
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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.