About the Role :

We are establishing an Agentic AI Center of Excellence (CoE) to design, build, and deploy the next generation of autonomous digital workers across RAAPID. We are seeking a hands-on, product-minded Manager, Agentic AI Products to design, build, and ship intelligent AI agent systems that solve real problems across verticals like Sales, Marketing, Product, Operations, HR, Legal, and Finance.

Key Responsibilities :

Agentic AI Architecture & Development :

- Design, build, and deploy production-grade agentic AI systems using frameworks such as LangGraph, LangChain, CrewAI, or custom orchestration layers, with well-defined tool-use patterns, planning mechanisms, state management, and error recovery.

- Build and maintain RAG pipelines integrated with agentic systems - including chunking strategies, embedding model selection, vector store management, and retrieval optimization.

- Implement guardrails, observability, and evaluation frameworks to ensure agent reliability, safety, and performance in production.

Product Management & Strategy:

- Own the product roadmap for RAAPID's agentic AI capabilities - from discovery through launch, iteration, and scale.

- Identify and scope high-impact agentic product opportunities across business functions - decomposing complex cross-functional workflows into well-defined agent tasks, tool integrations, and automation candidates.

- Conduct user research, analyze product usage data, and run experiments to continuously improve agent performance and user outcomes.

- Own the product spec for every agent we ship - define what it does, how we measure it, and work with stakeholders to prioritize the build order.

- Deliver executive-level reporting on product impact - connecting agent performance to pipeline, revenue, and customer ROI.

- Build and maintain a competitive intelligence framework - track how competitors are adopting agentic and GenAI capabilities, and use those insights to inform product positioning and feature prioritization.

- Partner with customer success and sales teams to establish closed-loop feedback cycles - capture deployment learnings, user friction points, and feature requests from live customer environments to continuously shape the product backlog.

Cross-Functional Leadership & Innovation:

- Lead and mentor a team of AI engineers and product contributors building agentic products.

- Collaborate closely with engineering, sales, customer success, and leadership to ensure agentic products align with GTM strategy and customer needs.

- Serve as the company's internal expert on agentic AI - advising on architecture decisions, emerging patterns, and competitive landscape.

- Stay at the forefront of agentic AI advancements and translate them into product opportunities.

- Structure team workflows to balance experimentation with delivery commitments using Agile/Scrum methodologies.

Required Qualifications:

- 3+ years of hands-on experience designing and building agentic AI systems.

- MBA from a Tier 1 business school or premier institution is preferred.

- Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field.

- Strong product management skills - proven ability to own a product roadmap, write PRDs, define metrics, and ship products.

- Deep technical fluency with LLMs, RAG architectures, prompt engineering, and at least one agent framework (LangGraph, LangChain, CrewAI, AutoGen, or equivalent).

- Experience deploying AI systems to production with attention to latency, cost, reliability, and observability.

- Strong analytical skills with the ability to turn data into product decisions.

- Experience in the healthcare technology, SaaS, or enterprise AI industry.

Technical Skills :

Agent Frameworks & AI :

- LangGraph, LangChain, CrewAI, AutoGen, or custom orchestration

- LLMs (Gemini, Claude, open-source models), RAG pipelines, prompt engineering, fine-tuning

- Tool-use patterns, function calling, MCP (Model Context Protocol)

Engineering & Infrastructure :

- Python, with working knowledge of APIs, async patterns, and data pipelines

- Vector databases (Pinecone, Weaviate, ChromaDB, pgvector)

- Cloud platforms: AWS, Azure, or GCP

- Observability & evaluation: LangSmith, Weights & Biases, custom tracing

Product & Data :

- Product management tools: Clickup, Visio, Linear, Figma

- Data analysis: SQL, Pandas, basic BI tools (Tableau, PowerBI)

- Experimentation frameworks and A/B testing for AI systems

Core Competencies :

- Innovation & Curiosity: Stays ahead of the rapidly evolving agentic AI landscape

- AI Product Sense: Ability to identify where agentic AI creates real value vs. where simpler solutions suffice

- Technical Architecture Thinking: Can whiteboard an agent system and also write the code

- Strategic Thinking: Connects technical capabilities to business outcomes and customer needs

- Builder Mentality: Bias toward shipping and iterating over theorizing

- Cross-Functional Collaboration: Works effectively across engineering, sales, and leadership

- Data-Driven Decision Making: Uses metrics and evidence to prioritize and evaluate