
Product Manager- AI Native Automation and Agentic System
2 days ago
About the role:
We're seeking a forward-thinking Product Manager who deeply understands AI-native product
development and has a bias for automation, agentic workflows, and self-improving systems.
This role is about owning the vision for AI-powered, autonomous decision-making features across
our HVAC, energy optimization and IoT platforms.
You'll work at the intersection of GenAI, IoT, and
intelligent automation, driving end-to-end product ownership — from ideation and data strategy to
AI-first experience design, deployment and delivery.
As a product manager you will focus customer benefits through customer first product innovation.
You will be responsible for feature adoption, activation rates and time to value.
Key Responsibilities of the role will include:
AI-Native Product Ownership
• Define the product vision and roadmap for agentic automation features and AI copilots within
the IoT and analytics ecosystem.
• Own end-to-end product lifecycle — from ideation → design → orchestration → delivery →
learning loops.
• Continuously identify opportunities in the overall product to replace static workflows with
self-improving AI-driven automation.
AI Orchestration & Integration
● Work closely with AI/ML teams to integrate ML based models, LLMs, multimodal models, and
context-aware agents into product experiences.
● Design autonomous decision-making loops leveraging real-time IoT data, predictive ML models,
and user feedback.
● Ensure the AI stack balances cost, performance, explainability, and safety.
Data-Driven Insights & Metrics
● Define and track AI-specific KPIs to track improvements and feature success.
● Work closely with AI/ML teams to use data pipelines, vector databases, and analytics tools to
create AI-powered dashboards that inform roadmap priorities.
Cross-Functional Leadership
● Collaborate with engineering, AI, IoT, and analytics teams to ship autonomous, intelligent
features at speed.
● Actively work with stakeholders to align on outcomes, but maintain independent product
opinions driven by AI insights and emerging tech.
● Act as a thought partner to leadership, steering strategic bets in AI-native transformation.
Required Skills & Qualification
Specific requirements include:
Core Competencies
● 4 to 7 years of product management experience in AI/ML, IoT, automation, or digital platforms.
● AI-native product thinking → Understand how to leverage Gen AI, NN or ML to improve the
product experience and utility.
● End-to-end ownership of AI-powered features.
● Doesn't need to code, but must understand the capabilities, trade-offs, and orchestration of
AI systems well enough to drive roadmap decisions and challenge engineering assumptions.
● Encourages experimentation pipelines powered by AI → using LLMs, simulations, and rapid
scenario testing to make data-backed, faster decisions.
● Strong foundation in Agile, Scrum, and product development best practices, but thinks beyond
conventional Jira-driven workflows.
● Understands how AI accelerates the traditional product lifecycle → enabling faster discovery,
prototyping, validation, and iteration.
Technical Fluency
● Basic understanding of APIs, rising AI tools, and agent orchestration frameworks.
● Comfortable working with data pipelines, time-series telemetry, and LLM integration
strategies.
● Actively explores emerging AI platforms, APIs, and automation stacks to stay ahead of industry
trends and bring fresh solutions into the product.
● Comfortable automating personal workflows — from analytics summarization and
documentation generation to user research synthesis and competitive scanning.
Stakeholder & Leadership Skills
● Exceptional communication — ability to translate AI complexity into business outcomes.
● Self-driven, opinionated PM who doesn't just collect requirements but shapes solutions.
● Strong collaboration with AI engineers, IoT specialists, and leadership teams to balance speed,
intelligence, and scalability.
Bonus points for
● Prior experience in agentic system design — copilots, autonomous decision engines, or AI
automation layers.
● Familiarity with energy optimization workflows or IoT telemetry systems.
● Knowledge of AI safety, interpretability, and ethical automation principles.
● Hands-on familiarity with AI stacks — OpenAI, LangChain, Pinecone/Weaviate, Chroma, Airflow,
cloud-native workflows.
● Familiarity with cloud-native environments (AWS, GCP, Azure) and event-driven architectures.
● Exposure to sustainability, HVAC and energy efficiency solutions and services w
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