AI Automation & Agentic AI Lead

Job Description: AI Automation & Agentic AI Lead

Experience: 7+ Years in Technology, with 3+ Years in GenAI / AI Automation

Location: Bangalore – Hybrid

Role: AI Architecture, Agentic AI & Enterprise Automation

Role Summary

We are looking for an experienced AI Automation & Agentic AI Lead to architect, develop, and govern enterprise-grade AI solutions using Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP). The role involves leading AI architecture and delivery, building intelligent agents and automation workflows, and ensuring enterprise security, scalability, governance, and responsible AI practices.

Key Responsibilities

1. AI Architecture & Delivery

• Architect and implement scalable GenAI and Agentic AI solutions for enterprise use cases.
• Design end-to-end AI platforms integrating LLMs, RAG pipelines, AI agents, and enterprise systems.
• Lead AI solution delivery from proof of concept through production deployment.
• Define reusable architecture patterns, engineering standards, and integration frameworks.

2. Agentic AI & Automation

• Design and develop intelligent agents and multi-agent workflows for business process automation.
• Build AI assistants integrated with enterprise tools, APIs, and knowledge bases.
• Implement tool calling, agent memory, reasoning patterns, and workflow orchestration.
• Drive AI-powered decision-making and automation to improve operational efficiency.

3. RAG & Enterprise AI Platforms

• Design and optimize RAG architectures, embedding pipelines, semantic search, and retrieval strategies.
• Work with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, or Chroma.
• Integrate LLMs and AI agents with enterprise applications, data platforms, and APIs.
• Ensure AI solutions are scalable, reliable, observable, and production-ready.

4. AI Governance, Security & Leadership

• Establish AI governance, Responsible AI, security, compliance, and data protection practices.
• Define standards for MCP architecture, agent access control, RBAC, auditability, and secure tool execution.
• Implement appropriate safeguards for enterprise AI integrations and sensitive data.
• Mentor engineering teams and provide technical leadership across AI programs.

5. Cloud & Platform Engineering

• Leverage cloud platforms such as Azure, AWS, and GCP to deploy and operate AI solutions.
• Work with Kubernetes/OpenShift and enterprise APIs to support scalable AI workloads.
• Apply platform engineering, SRE, AIOps, or DevOps principles to improve reliability and operational excellence.

Required Skills

• Strong hands-on experience with Generative AI, LLMs, prompt engineering, and AI orchestration frameworks.
• Expertise in Agentic AI, AI agents, multi-agent workflows, tool calling, memory, and reasoning patterns.
• Strong experience designing and implementing RAG architectures, embeddings, semantic search, and vector databases.
• Good understanding of MCP architecture and enterprise AI integration patterns.
• Experience delivering production-grade GenAI and AI automation solutions.
• Knowledge of AI governance, Responsible AI, security, RBAC, auditability, compliance, and data protection.
• Experience with Azure, AWS, or GCP, along with Kubernetes/OpenShift and API integrations.
• Strong architecture, problem-solving, stakeholder management, and technical leadership skills.

📩 Interested candidates can reach out via DM or share their updated resume at [email protected]. Immediate joiners are preferred.