Generative AI - Senior Manager
On-siteBengaluru, Karnataka, India
Job Summary
Lead evaluation, benchmarking, and implementation of scalable, secure, and compliant Agentic AI frameworks aligned with enterprise business use cases. Drive technical standardization by creating reusable orchestration blueprints, prompt engineering guides, and integration patterns to ensure consistent delivery in complex programs. Define scalable multi-agent system design patterns including tool usage, memory management, task routing, and human-in-the-loop processes. Establish evaluation frameworks to assess solution performance, focusing on reasoning, tool reliability, and hallucination mitigation for production readiness. Design enterprise Retrieval Augmented Generation (RAG) architectures optimizing retrieval processes, embeddings, and reranking aligned with data governance. Manage client engagements including discovery, demos, proposal development, and delivery planning, leveraging strong DevOps, LLMOps, and CI/CD pipeline expertise to ensure successful partnerships.
Required Qualifications
- At least a Bachelor's & Master's degree
- 12+ years of experience in technical/technology roles
- Oral and written proficiency in English
Desired Qualifications
- Proven experience with enterprise cloud AI platforms like Azure AI Foundry (with Microsoft Fabric and Purview), Amazon Bedrock (with Knowledge Bases and Guardrails), and Google Vertex AI (with BigQuery and Agentspace) for building, governing, and deploying scalable production-grade Gen AI and Agentic AI solutions
- Hands-on expertise with leading agentic and AI orchestration frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalents for AI workflow automation and orchestration
- In-depth knowledge of vector databases (Pinecone, Weaviate, Milvus, Azure AI Search) and their application in enterprise Retrieval - Augmented Generation (RAG) and knowledge retrieval systems
- Experience designing and scaling AI solutions that utilize multi-modal capabilities across text, vision, audio, and document understanding to enhance AI functionality
- Familiarity with AI governance and observability platforms (e.g., LangSmith, Arize) to enable monitoring, tracing, debugging, and compliance of production AI systems, along with expertise in selecting appropriate LLMs (GPT, Claude, Gemini, etc.) based on enterprise cost, latency, and compliance requirements
- Knowledge of AI-powered development tools (GitHub Copilot, Cursor, Windsurf) to improve engineering productivity and facilitate large-scale AI-driven software development
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