EY Manager - Business Consulting PI TMT CNS BC Finance Bangalore 

India, Karnataka, Bengaluru 

64191607

Requisition Id : 1631494

TMT :

Industry convergence offers TMT (Technology, Media & Entertainment, and Telecommunications) organizations the chance to evolve and transform, but it also presents challenges around competitiveness and delivering agile corporate strategies for growth.

CNS - BC - Finance :

It has multiple fields of play such as:

Supply Chain and Operations - we provide a unique combination of industry-specific, strategic, operational and financial insights, digital technology advances and strategic alliance partners to deliver better outcomes and also help clients effect fundamental change in their operations’ performance to support sales growth, become more cost competitive, minimize risk and ensure operational resilience.

Your key responsibilities

Technical Excellence

Location: Bangalore, Working from office Mandatory. Experience Level: 6-8 years Job Summary We are seeking a passionate and highly skilled Solution Architect – Generative AI & Agentic AI to design, develop, and deploy intelligent systems leveraging large language models (LLMs), multiagent frameworks, and enterprise AI integration patterns. This role will play a key part in building next-generation AI applications that autonomously reason, act, and learn across complex business workflows. As a Generative?&?Agentic?AI?Solution Architect you will own the end-to-end architecture for enterprise-grade GenAI solutions and multi-agent systems. You’ll translate business objectives into scalable, compliant, and observable AI capabilities—spanning data pipelines, foundation-model ops, Retrieval-Augmented?Generation (RAG), and autonomous agent orchestration. You will partner with product owners, data scientists, platform engineers, security, and business stakeholders to accelerate AI-driven transformation while safeguarding performance, ethics, and regulatory compliance. Key Responsibilities: Solution Development: • Design and implement applications using LLMs (e.g., OpenAI, Mistral, Claude, Llama). • Build autonomous multi-agent systems using frameworks like AutoGen, LangGraph, CrewAI, or AgentOps. • Develop scalable backend services and orchestration pipelines using Python/Node.js integrated with AI APIs. • Lead discovery workshops, create MVP backlogs, and convert PoCs into production-ready solutions following MLOps / LLMOps best practices. • Oversee model selection, finetuning, prompt-engineering, evaluation, and continuous monitoring. Architecture & Engineering: • Translate business requirements into agentic workflows with reasoning, memory, and tool usage. • Integrate GenAI and agents with enterprise systems (e.g., SAP, ServiceNow, Salesforce) via APIs and RAG pipelines. • Work with vector databases (e.g., Pinecone, FAISS, Weaviate) for semantic search and long-term memory. • Define reference architectures for GenAI (LLMs, Diffusion, SSMs) and agentic patterns (task-decomposition, planner-executor, tool-calling). • Design secure micro-service and event-driven topologies on cloud / hybrid infra (AWS Bedrock, Azure OpenAI, Google Vertex, private GPUs). Required?Technical?Competencies: • Generative?AI: Hands-on with LLMs (GPT-4o, Claude-3, Gemini, Llama-3), Diffusion, and audio-/vision models; experience with HF Transformers, LangChain / LlamaIndex. • Agentic?Frameworks: Experience designing goal-oriented agents using AutoGen, CrewAI, Semantic?Kernel, or custom planners; familiarity with tool-calling, memory management, and AI?schedulers. • LLMOps / MLOps: CI/CD for model artifacts, feature stores, vector DBs (Pinecone, Weaviate, FAISS), model gateways, and policy engines (Guardrails, Azure?AI?Safety). • Cloud & DevSecOps: Terraform, Kubernetes, Docker, serverless, GPU orchestration, secret management, SAST/DAST integration. • Programming: Python (primary), TypeScript/Node, Bash; strong design-pattern discipline and code-review leadership. • Build replaceable but working proof-of-concepts—CLI, Streamlit, or VS Code Jupyter—so stakeholders can “touch” the idea. • Write production-grade Python/TypeScript to orchestrate agents with AutoGen / CrewAI / Semantic?Kernel. • Hook agents to real systems (SAP BAPIs, Salesforce APIs, REST/GraphQL) and manage auth tokens & secrets. • Build CI/CD (GitHub?Actions, Terraform, Helm) that auto-tests prompts, pushes Docker images, and provisions GPUs. • Instrument tracing (OpenTelemetry) and set up dashboards for tokens, latency, cost per call. Education: • Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.

Skills and attributes

To qualify for the role you must have
Qualification

Location: Bangalore, Working from office Mandatory. Experience Level: 6-8 years Job Summary We are seeking a passionate and highly skilled Solution Architect – Generative AI & Agentic AI to design, develop, and deploy intelligent systems leveraging large language models (LLMs), multiagent frameworks, and enterprise AI integration patterns. This role will play a key part in building next-generation AI applications that autonomously reason, act, and learn across complex business workflows. As a Generative?&?Agentic?AI?Solution Architect you will own the end-to-end architecture for enterprise-grade GenAI solutions and multi-agent systems. You’ll translate business objectives into scalable, compliant, and observable AI capabilities—spanning data pipelines, foundation-model ops, Retrieval-Augmented?Generation (RAG), and autonomous agent orchestration. You will partner with product owners, data scientists, platform engineers, security, and business stakeholders to accelerate AI-driven transformation while safeguarding performance, ethics, and regulatory compliance. Key Responsibilities: Solution Development: • Design and implement applications using LLMs (e.g., OpenAI, Mistral, Claude, Llama). • Build autonomous multi-agent systems using frameworks like AutoGen, LangGraph, CrewAI, or AgentOps. • Develop scalable backend services and orchestration pipelines using Python/Node.js integrated with AI APIs. • Lead discovery workshops, create MVP backlogs, and convert PoCs into production-ready solutions following MLOps / LLMOps best practices. • Oversee model selection, finetuning, prompt-engineering, evaluation, and continuous monitoring. Architecture & Engineering: • Translate business requirements into agentic workflows with reasoning, memory, and tool usage. • Integrate GenAI and agents with enterprise systems (e.g., SAP, ServiceNow, Salesforce) via APIs and RAG pipelines. • Work with vector databases (e.g., Pinecone, FAISS, Weaviate) for semantic search and long-term memory. • Define reference architectures for GenAI (LLMs, Diffusion, SSMs) and agentic patterns (task-decomposition, planner-executor, tool-calling). • Design secure micro-service and event-driven topologies on cloud / hybrid infra (AWS Bedrock, Azure OpenAI, Google Vertex, private GPUs). Required?Technical?Competencies: • Generative?AI: Hands-on with LLMs (GPT-4o, Claude-3, Gemini, Llama-3), Diffusion, and audio-/vision models; experience with HF Transformers, LangChain / LlamaIndex. • Agentic?Frameworks: Experience designing goal-oriented agents using AutoGen, CrewAI, Semantic?Kernel, or custom planners; familiarity with tool-calling, memory management, and AI?schedulers. • LLMOps / MLOps: CI/CD for model artifacts, feature stores, vector DBs (Pinecone, Weaviate, FAISS), model gateways, and policy engines (Guardrails, Azure?AI?Safety). • Cloud & DevSecOps: Terraform, Kubernetes, Docker, serverless, GPU orchestration, secret management, SAST/DAST integration. • Programming: Python (primary), TypeScript/Node, Bash; strong design-pattern discipline and code-review leadership. • Build replaceable but working proof-of-concepts—CLI, Streamlit, or VS Code Jupyter—so stakeholders can “touch” the idea. • Write production-grade Python/TypeScript to orchestrate agents with AutoGen / CrewAI / Semantic?Kernel. • Hook agents to real systems (SAP BAPIs, Salesforce APIs, REST/GraphQL) and manage auth tokens & secrets. • Build CI/CD (GitHub?Actions, Terraform, Helm) that auto-tests prompts, pushes Docker images, and provisions GPUs. • Instrument tracing (OpenTelemetry) and set up dashboards for tokens, latency, cost per call. Education: • Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.

Location: Bangalore, Working from office Mandatory. Experience Level: 6-8 years Job Summary We are seeking a passionate and highly skilled Solution Architect – Generative AI & Agentic AI to design, develop, and deploy intelligent systems leveraging large language models (LLMs), multiagent frameworks, and enterprise AI integration patterns. This role will play a key part in building next-generation AI applications that autonomously reason, act, and learn across complex business workflows. As a Generative?&?Agentic?AI?Solution Architect you will own the end-to-end architecture for enterprise-grade GenAI solutions and multi-agent systems. You’ll translate business objectives into scalable, compliant, and observable AI capabilities—spanning data pipelines, foundation-model ops, Retrieval-Augmented?Generation (RAG), and autonomous agent orchestration. You will partner with product owners, data scientists, platform engineers, security, and business stakeholders to accelerate AI-driven transformation while safeguarding performance, ethics, and regulatory compliance. Key Responsibilities: Solution Development: • Design and implement applications using LLMs (e.g., OpenAI, Mistral, Claude, Llama). • Build autonomous multi-agent systems using frameworks like AutoGen, LangGraph, CrewAI, or AgentOps. • Develop scalable backend services and orchestration pipelines using Python/Node.js integrated with AI APIs. • Lead discovery workshops, create MVP backlogs, and convert PoCs into production-ready solutions following MLOps / LLMOps best practices. • Oversee model selection, finetuning, prompt-engineering, evaluation, and continuous monitoring. Architecture & Engineering: • Translate business requirements into agentic workflows with reasoning, memory, and tool usage. • Integrate GenAI and agents with enterprise systems (e.g., SAP, ServiceNow, Salesforce) via APIs and RAG pipelines. • Work with vector databases (e.g., Pinecone, FAISS, Weaviate) for semantic search and long-term memory. • Define reference architectures for GenAI (LLMs, Diffusion, SSMs) and agentic patterns (task-decomposition, planner-executor, tool-calling). • Design secure micro-service and event-driven topologies on cloud / hybrid infra (AWS Bedrock, Azure OpenAI, Google Vertex, private GPUs). Required?Technical?Competencies: • Generative?AI: Hands-on with LLMs (GPT-4o, Claude-3, Gemini, Llama-3), Diffusion, and audio-/vision models; experience with HF Transformers, LangChain / LlamaIndex. • Agentic?Frameworks: Experience designing goal-oriented agents using AutoGen, CrewAI, Semantic?Kernel, or custom planners; familiarity with tool-calling, memory management, and AI?schedulers. • LLMOps / MLOps: CI/CD for model artifacts, feature stores, vector DBs (Pinecone, Weaviate, FAISS), model gateways, and policy engines (Guardrails, Azure?AI?Safety). • Cloud & DevSecOps: Terraform, Kubernetes, Docker, serverless, GPU orchestration, secret management, SAST/DAST integration. • Programming: Python (primary), TypeScript/Node, Bash; strong design-pattern discipline and code-review leadership. • Build replaceable but working proof-of-concepts—CLI, Streamlit, or VS Code Jupyter—so stakeholders can “touch” the idea. • Write production-grade Python/TypeScript to orchestrate agents with AutoGen / CrewAI / Semantic?Kernel. • Hook agents to real systems (SAP BAPIs, Salesforce APIs, REST/GraphQL) and manage auth tokens & secrets. • Build CI/CD (GitHub?Actions, Terraform, Helm) that auto-tests prompts, pushes Docker images, and provisions GPUs. • Instrument tracing (OpenTelemetry) and set up dashboards for tokens, latency, cost per call. Education: • Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.

What we look for

People with the ability to work in a collaborative manner to provide services across multiple client departments while following the commercial and legal requirements. You will need a practical approach to solving issues and complex problems with the ability to deliver insightful and practical solutions. We look for people who are agile, curious, mindful and able to sustain postivie energy, while being adaptable and creative in their approach.

What we offer

If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.