Lead AI Architect
Dentsu
Lead AI Architect
Job Description
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.Job Description:Experience - 10-15 YearsLocation: Bengaluru, Pune, MumbaiMode of Work - HybridMandate Background - The person should be from a Data Engineering/ Data Science Background before moving to AgenticAI/GenAIRole SummaryServe 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 ResponsibilitiesLead technical architecture for multi-agent systems, LLM orchestration, and AI automation workflowsSet up and maintain the agentic engineering stack: frameworks, CI/CD, testing, monitoring, and deployment patternsOwn the technical design for AI orchestration use cases across 4+ client implementationsBuild and maintain reusable agent components, tool-use libraries, and prompt templatesLead Genie space setup and configuration for client data explorationMentor Senior Agentic Engineers, conducting code reviews and architecture discussionsEvaluate LLM providers (model selection, cost optimization, latency tradeoffs) and recommend choicesBridge the gap between Data Science model outputs and agentic deployment, ensuring models are served efficientlyCollaborate with the onshore Senior AI Engineer on shared architecture decisions and technical standardsContribute to technical documentation, runbooks, and operational playbooks for the agentic platformRequired Qualifications7+ years of software engineering experience with at least 3 years in AI/ML engineeringDeep expertise in Python and production-grade software architectureHands-on experience building and deploying LLM-powered applications at scaleStrong knowledge of agent orchestration patterns (LangChain, LangGraph, AutoGen, or custom frameworks)Experience with cloud infrastructure (Azure preferred) including container orchestration and serverless patternsTrack record of mentoring engineers and raising team engineering standardsExperience with MLOps: model serving, monitoring, versioning, and cost managementStrong system design skills with experience in distributed systems and API architectureExcellent written communication for technical documentation and cross-timezone collaborationPreferred QualificationsExperience with Databricks, Unity Catalog, and/or GenieBackground in media technology, adtech, or marketing analytics platformsExperience with RAG architectures, vector databases, and semantic search at scaleContributions to open-source AI/ML projectsExperience leading technical teams in a DGS/offshore delivery modelLocation:DGS India - Mumbai - Thane Ashar IT ParkBrand:MerkleTime Type:Full timeContract Type:Permanent
Locations
- DGS India - Mumbai - Thane Ashar IT Park
- Pune
Skills Required
- at least 3 years in AI/ML engineeringintermediate
- Pythonintermediate
- and deploying LLM-powered applications at scaleintermediate
- agent orchestration patternsintermediate
- cloud infrastructureintermediate
- MLOps: model servingintermediate
- distributed systemsintermediate
- Databricksintermediate
- media technologyintermediate
- RAG architecturesintermediate
Required Qualifications
- 7+ years of software engineering experience with at least 3 years in AI/ML engineering (experience, 7 years)
- Deep expertise in Python and production-grade software architecture (experience)
- Hands-on experience building and deploying LLM-powered applications at scale (experience)
- Strong knowledge of agent orchestration patterns (LangChain, LangGraph, AutoGen, or custom frameworks) (experience)
- Experience with cloud infrastructure (Azure preferred) including container orchestration and serverless patterns (experience)
- Track record of mentoring engineers and raising team engineering standards (experience)
- Experience with MLOps: model serving, monitoring, versioning, and cost management (experience)
- Strong system design skills with experience in distributed systems and API architecture (experience)
- Excellent written communication for technical documentation and cross-timezone collaboration (experience)
- 7+ years of software engineering experience with at least 3 years in AI/ML engineering (experience, 7 years)
- Deep expertise in Python and production-grade software architecture (experience)
- Hands-on experience building and deploying LLM-powered applications at scale (experience)
- Strong knowledge of agent orchestration patterns (LangChain, LangGraph, AutoGen, or custom frameworks) (experience)
- Experience with cloud infrastructure (Azure preferred) including container orchestration and serverless patterns (experience)
- Track record of mentoring engineers and raising team engineering standards (experience)
- Experience with MLOps: model serving, monitoring, versioning, and cost management (experience)
- Strong system design skills with experience in distributed systems and API architecture (experience)
- Excellent written communication for technical documentation and cross-timezone collaboration (experience)
Preferred Qualifications
- Experience with Databricks, Unity Catalog, and/or Genie (experience)
- Background in media technology, adtech, or marketing analytics platforms (experience)
- Experience with RAG architectures, vector databases, and semantic search at scale (experience)
- Contributions to open-source AI/ML projects (experience)
- Experience leading technical teams in a DGS/offshore delivery model (experience)
- Experience with Databricks, Unity Catalog, and/or Genie (experience)
- Background in media technology, adtech, or marketing analytics platforms (experience)
- Experience with RAG architectures, vector databases, and semantic search at scale (experience)
- Contributions to open-source AI/ML projects (experience)
- Experience leading technical teams in a DGS/offshore delivery model (experience)
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
- 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
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