AI Product Engineer

SquadStack.ai; Dadri; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

SquadStack.ai is seeking an AI Product Manager to own end-to-end lifecycle of AI-powered products. You will define vision, roadmaps, requirements, and launches, working with engineering, data science, and sales to deliver value for enterprise clients.

You will identify practical AI use cases, leverage LLMs, prompt engineering, AI agents, and RAG, drive adoption, measure impact, and collaborate with stakeholders to ensure timely delivery and measurable business outcomes.

Qualifications

• Experience leading AI product strategy and lifecycle.
• Ability to translate client needs into AI-based product solutions.
• Track record of delivering measurable impact through AI deployments.

Responsibilities

• Own end-to-end product lifecycle for AI-powered products, from vision to launch.
• Identify and develop practical AI use cases using LLMs, prompts, and AI workflows.
• Engage enterprise clients to translate needs into scalable AI solutions.
• Coordinate with Engineering, AI/ML, Data Science, Sales, and Success teams.
• Track adoption and business metrics to drive measurable improvements.

Skills

AI Product Mgmt

LLMs

Prompt Engineering

AI Agents

RAG

Conversational AI

Enterprise AI Deployment

Stakeholder Mgmt

Client Mgmt

Product Strategy

Roadmapping

Data-driven Decisions

Job description

Responsibilities:

• Product Strategy and Ownership: Own the end-to-end product lifecycle, including product vision, roadmap, prioritization, requirements, execution, launch, and continuous improvement of AI-powered products.
• AI Product Development: Identify and develop practical AI use cases using LLMs, prompt engineering, AI agents, RAG, conversational AI, and AI workflows to solve customer and business problems.
• Enterprise and Client Engagement: Work closely with enterprise customers and clients to understand their business requirements, identify AI opportunities, translate needs into product solutions, and drive successful AI deployment and adoption.
• Cross-functional and Stakeholder Management: Collaborate with Engineering, AI/ML, Data Science, Sales, Customer Success, and Leadership teams to define requirements, manage priorities, resolve dependencies, and ensure timely product delivery.
• Product Performance and Impact: Track product adoption, customer feedback, engagement, and business metrics; use data-driven insights to optimize AI solutions and deliver measurable improvements in customer and business outcomes.

Requirements:

• Key Skills: AI/GenAI Product Management, LLMs, Prompt Engineering, AI Agents, RAG, Conversational AI, Enterprise AI Deployment, Stakeholder Management, Client Management, Product Strategy, Roadmapping, Data-driven Decision Making.