Agentic AI Architect

Job Description:

Location: Bengaluru, Mumbai, Pune, Gurugram

Experience - 12-15 years

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 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 and technically lead 3 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

• 10 - 12 years of software engineering experience with at least 4 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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