Lead Enterprise Solutions Applied AI Engineer

Overview

Hands-on, forward-deployed technical leader who designs, builds and deploys production-grade agentic AI solutions across the enterprise, working directly with business units and setting standards for responsible scaling.

What you'll do

• Lead agentic AI initiatives as the embedded technical leader within business units, overseeing the full lifecycle from idea to implementation and monitoring.
• Connect AI agents to diverse enterprise platforms (e.g., Salesforce, SAP, legacy databases, APIs), ensuring seamless integration and production-ready performance through rapid iteration and troubleshooting.
• Oversee pilot launches, provide user training, and develop thorough documentation to support adoption and transition of AI solutions to business stakeholders.
• Design and build multi-agent AI systems that automate complex business processes, emphasizing agent orchestration and human in the loop concepts.
• Transform human workflows into agent-first processes and identify necessary human oversight points.
• Develop evaluation tools and optimize solutions for performance and cost, maintaining high quality throughout deployment and operation.
• Extract successful patterns from fieldwork to create libraries, templates, and reference implementations for other teams.
• Define production-ready reference architectures and official checklists for security, reliability, and operability.
• Partner with Security and Governance teams to embed safety guardrails, audit logging, and compliance checks into core agent architectures.
• Author best practices, lead technical reviews, and mentor other engineers to help them ship agentic solutions independently.

What you'll need

• Over 10 years of experience in software engineering.
• More than 5 years building AI and machine learning systems.
• 3+ years delivering AI solutions that create real business results in production.
• Leadership experience guiding technical direction and aligning teams.
• Skilled with large language models (LLMs), prompt engineering, and agent frameworks like LangChain and LlamaIndex.
• Hands-on with Retrieval-Augmented Generation (RAG) and using tools or functions within AI agents.
• Proficient in Python, with strong knowledge of frontend development for agent UIs (React, TypeScript, APIs, authentication) and building reliable production systems.
• Experience integrating with business systems (CRMs, ERPs, HR platforms).
• Strong understanding of enterprise security, compliance, and data governance.
• Deep understanding of OpenAI, Anthropic Claude, Azure OpenAI, and agent frameworks such as Microsoft Agent Framework, Vertex AI Agent Builder, and Semantic Kernel.
• Knowledge of vector databases like MongoDB, Pinecone, Weaviate, and Qdrant, and graph databases for knowledge representation.
• Experienced with cloud services (Azure, GCP), container tools (Docker, Kubernetes), and CI/CD pipelines.
• Skilled with logging, tracing, and monitoring tools for AI applications.
• Bachelor's degree in Computer Science, Industrial Technology or Engineering, or a related field (or equivalent practical experience).

Details

• Hybrid role.
• Location: Bangalore, India.