Lead AI Architect

Job Description:

Experience - 10-15 Years

Location: Bengaluru, Pune, Mumbai

Mode of Work - Hybrid

Mandate Background - The person should be from a Data Engineering/ Data Science Background before moving to AgenticAI/GenAI

Role Summary

Serve as the technical anchor for Dentsu's agentic AI engineering team in DGS. You will lead architecture decisions for multi-agent systems, set engineering standards, and mentor a growing team of agentic engineers. This is a hands-on leadership role: you write code, review code, and set the technical direction while the Senior Director handles the VP-level strategy and stakeholder management.

Key Responsibilities

• Lead technical architecture for multi-agent systems, LLM orchestration, and AI automation workflows

• Set up and maintain the agentic engineering stack: frameworks, CI/CD, testing, monitoring, and deployment patterns

• Own the technical design for AI orchestration use cases across 4+ client implementations

• Build and maintain reusable agent components, tool-use libraries, and prompt templates

• Lead Genie space setup and configuration for client data exploration

• Mentor Senior Agentic Engineers, conducting code reviews and architecture discussions

• Evaluate LLM providers (model selection, cost optimization, latency tradeoffs) and recommend choices

• Bridge the gap between Data Science model outputs and agentic deployment, ensuring models are served efficiently

• Collaborate with the onshore Senior AI Engineer on shared architecture decisions and technical standards

• Contribute to technical documentation, runbooks, and operational playbooks for the agentic platform

Required Qualifications

• 7+ years of software engineering experience with at least 3 years in AI/ML engineering

• Deep expertise in Python and production-grade software architecture

• Hands-on experience building and deploying LLM-powered applications at scale

• Strong knowledge of agent orchestration patterns (LangChain, LangGraph, AutoGen, or custom frameworks)

• Experience with cloud infrastructure (Azure preferred) including container orchestration and serverless patterns

• Track record of mentoring engineers and raising team engineering standards

• Experience with MLOps: model serving, monitoring, versioning, and cost management

• Strong system design skills with experience in distributed systems and API architecture

• Excellent written communication for technical documentation and cross-timezone collaboration

Preferred Qualifications

• Experience with Databricks, Unity Catalog, and/or Genie

• Background in media technology, adtech, or marketing analytics platforms

• Experience with RAG architectures, vector databases, and semantic search at scale

• Contributions to open-source AI/ML projects

• Experience leading technical teams in a DGS/offshore delivery model

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