AI Lead Architect
Dentsu · Media, Advertising & Entertainment
- Pune
- Hybrid
- Posted today
- Data & AI
About the job
Job Description:
Key Responsibilities
o Lead the hands-on engineering for end-to-end AI solutions across Deep Learning,
GenAI, Agentic AI, and multimodal use cases.
o Apply rigorous "fail fast" logic to all AI project management. Quickly identify,
evaluate, and disqualify unviable AI use cases based on technical feasibility, effort,
cost, and risk early in the cycle.
o Perform explicit trade-off analysis on model class (frontier vs. SLM vs. fine-tuned),
retrieval design, memory optimization, and orchestration.
o Lead solutioning, support architecture for end-to-end AI solutions across GenAI,
Agentic AI, multimodal, and applied ML use cases, with explicit trade-off analysis
on model class (frontier vs. SLM vs. fine-tuned), retrieval design, memory, and
orchestration.
o Own the practice's reference architectures and solution design patterns for
multimodal agentic systems, including planning, tool use, memory, grounding, and
inter-agent communication (MCP, A2A).
o Conduct solution design reviews across concurrent client engagements; facilitate
subjective technical decisions and enable delivery excellence.
o Design and lead the build of multi-agent systems with reasoning, planning, tool
use, persistent memory, and grounded retrieval.
o Lead multimodal system design and solutions across text, vision, speech, and
structured data, including ingestion, representation, and downstream agent
reasoning.
o Establish patterns for SLM design and adoption — distillation, fine-tuning,
quantization, and routing — to meet enterprise constraints on cost, latency, data
residency, and on-prem/edge deployment
o Define hybrid retrieval and knowledge architectures spanning vector, graph (KG),
and NoSQL stores; lead KG-assisted retrieval, entity linking, and structured
grounding.
o Establish evaluation as a first-class discipline: design eval frameworks, golden
datasets, regression suites, automated and human-in-the-loop evals, and
observability for agentic and generative systems.
o Define and enforce safety, guardrail, and hallucination-control standards across
the practice; lead red-teaming and adversarial testing for high-stakes
deployments.
o Set the bar for production readiness—reliability, latency, cost, monitoring, drift
detection, and incident response—for AI systems in regulated, enterprise-grade
environments.
o Lead GPU/accelerator ops, model serving, and lifecycle automation for
deployment across cloud hyper-scalers, on-prem, and edge.
o Act as a technical sentinel for the AI practice, mentoring engineers through
rigorous code and architecture reviews to ensure permanent capability building
rather than temporary crisis management.
o Establish and enforce AI in SDLC frameworks on delivery projects.
o Engage with client and stakeholder leadership on architecture, feasibility, and risk;
communicate technical direction clearly to non-technical audiences.
o Support pre-sales and solutioning for new GenAI and Agentic AI opportunities,
including effort estimation, architectural framing, and capability storytelling.
Must Have
Technical Skills
Good to have:
Experience with commerce cloud ecosystems (Salesforce and
Adobe).
Attitude & Mindset
"AI hype."
the office in Pune, ensuring regular connection and cross-project knowledge.
Location:
Pune
Brand:
Merkle
Time Type:
Full time
Contract Type:
Permanent