Manager-Workflow Architect / Applied AI

1 day ago

Mumbai, IndiaStaff+

Responsibilities

Lead the design and delivery of enterprise-grade AI solutions using Power Platform, Copilot Studio, Azure AI, and Microsoft 365.
Design and implement scalable, end-to-end AI workflows covering reasoning, decision-making, task execution, prompts, models, orchestration, and application layers.
Translate business and research requirements into practical AI architectures and explain solutions clearly to clients and stakeholders.
Create prompt libraries, workflow templates, system instructions, control logic, governance guidelines, and reusable components.
Build evaluation and quality frameworks with test cases, benchmarks, validation, and regression mechanisms.
Design grounded-data and RAG workflows, context-management strategies, human-review processes, and guardrails for accurate AI outputs.
Make architecture and platform decisions across AI tools and ecosystems while optimizing performance, scalability, cost, compliance, and governance.
Enable multi-step automation through API integrations, tool usage, monitoring, observability, versioning, and lifecycle management.
Lead the transition of AI solutions from pilot to production with a focus on operational stability and reliability.
Collaborate with business stakeholders to align solutions to organizational goals, adoption needs, and measurable impact.

12–15 years of experience designing, orchestrating, and governing complex AI-driven workflows.
Deep expertise in LLM behavior, prompt engineering, system-level AI design, agentic systems, and multi-step reasoning orchestration.
Experience architecting and delivering enterprise AI solutions with Power Platform, Copilot Studio, Azure AI, and Microsoft 365.
Experience designing secure, scalable, compliant solutions across hybrid and multi-cloud environments.
Experience with RAG-based workflows, context management, API integrations, automation, evaluation frameworks, benchmarks, and test cases.
Ability to translate complex business and research requirements into production-grade AI architectures and client-friendly explanations.
Experience with monitoring, observability, governance, guardrails, versioning, lifecycle management, and Responsible AI practices.

Hybrid working model with flexibility and international exposure.
Merit-based, innovation-driven culture supporting creativity, continuous learning, and professional growth.
Opportunity to work with generative and agentic AI for global enterprise clients across 45 countries.

Google Cloud