Lead architecture and engineering for multi-agent LLM systems, build agent components and orchestration pipelines, set engineering standards, mentor senior engineers, evaluate LLM providers, and produce operational runbooks and deployment patterns for client implementations.
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
- 12 - 15 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
Location:
DGS India - Bengaluru - Manyata N1 BlockBrand:
MerkleTime Type:
Full timeContract Type:
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Lead architecture and engineering for multi-agent LLM systems: design orchestration, build reusable agent components, set CI/CD and deployment standards, evaluate LLM providers, mentor senior engineers, and produce operational runbooks and documentation for agentic AI deployments.
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