Description review
Technical Product Manager – AI & Agents
CAST · Remote · back to the listing
HR standards
49/100
poor
Title ↔ description
83/100
solid
Reads as
Product Manager
100% confident
What this role officially is
ICT product manager — ESCO, the EU occupation classification
ICT product managers analyse and define current and target status for ICT products, services or solutions. They estimate the cost effectiveness, points of risk, opportunities, strengths and weaknesses of products or services provided. ICT product managers create structured plans and establish time scales and milestones, ensuring optimisation of activities and resources.
Also known as: IT product manager, IT products manager, ICT product managers, ICT products manager, ICT products managers
How others title the same work
Large employers
- Staff Product Manager, Search Experiences Mozilla
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- Product Lead, Connect Stripe
- Product Manager - Compliance, Bridge Stripe
- Product Manager, Ecosystem Risk Stripe
Startups
- Technical Product Manager Careforce
- Product Manager Agave
- Product Manager AlgoTest
- Product Manager Aqua
- Product Manager Artisan
What the listing never says
- No section describes what the person would actually do. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
The Problem Worth Solving
Generative AI is a powerful reasoning engine — but it operates blind inside enterprise software. It can't map a million-line multi-technologies codebase, trace cross-technology dependencies, or quantify technical debt. When asked to help modernize a legacy application, it guesses.
The industry's answer has been RAG and vector databases. Useful — but approximate. Semantic similarity is not the same as architectural truth.
CAST's answer: give AI the exact structural blueprint of the application, derived deterministically from source code analysis across 150+ technologies. Not approximations. Actual call graphs, dependency maps, transaction flows — the ground truth of how software actually works. We call this Software Intelligence. We're now building the bridge that puts it directly in the hands of AI agents.
What You'll Be Building
As Technical Product Manager – AI & Agents, you'll own the product definition and roadmap for integrating CAST's platforms — CAST Imaging and CAST Highlight — into the agentic AI ecosystem. Concretely:
• MCP Server & Agentic integrations. CAST Imaging already exposes its structural insights via an MCP server, making any MCP-aware agent — GitHub Copilot, Claude Code, Gemini — structurally aware of the application it's working on. You'll drive what data gets exposed, how agents consume it, and what new capabilities this unlocks for developers, architects, and transformation teams.
• Hyperscaler partnerships. You'll manage and grow technical integrations with AWS and Google Cloud. Our published research with Google has already demonstrated that augmenting Gemini with CAST's structural analysis produces measurably deeper results on enterprise codebases. You'll be the product owner turning that into a repeatable offering.
• GSI co-innovation. Tier-1 global system integrators are at the forefront of industrializing AI in the software development lifecycle — at enterprise scale, across industries. You'll work directly with them to understand where AI-driven modernization breaks down in practice, what's missing, and where CAST intelligence fills the gap. They're one of your best proxies for real market needs, and a source of product ideas you won't find in analyst reports.
• Next-generation retrieval. Our research team is actively exploring approaches that go beyond standard RAG — combining deterministic structural graphs with semantic retrieval to give agents richer, more grounded context. You'll translate emerging research into product bets, defining what gets productized and when.
What We're Looking For
• Hands-on background in software engineering or architecture. You can read a call graph, understand what a dependency means in practice, and have opinions about technical debt.
• Experience with agentic AI, LLM integrations, or developer tooling — building products or shipping integrations.
• Ability to work across research, engineering, and commercial teams — and translate between all three.
• Fluent English. Our teams and partners are global.
Why This Role
The intersection of software intelligence and AI agents is where the next generation of enterprise software transformation will be decided. You'll work with a research team that publishes with Google Cloud, ships MCP integrations used by real enterprise customers, and is actively pushing the frontier on how AI understands software at scale.
The scope is real. The partners are serious. The problem is unsolved.
Reporting to: Head of R&D
Originally posted on Himalayas
Generative AI is a powerful reasoning engine — but it operates blind inside enterprise software. It can't map a million-line multi-technologies codebase, trace cross-technology dependencies, or quantify technical debt. When asked to help modernize a legacy application, it guesses.
The industry's answer has been RAG and vector databases. Useful — but approximate. Semantic similarity is not the same as architectural truth.
CAST's answer: give AI the exact structural blueprint of the application, derived deterministically from source code analysis across 150+ technologies. Not approximations. Actual call graphs, dependency maps, transaction flows — the ground truth of how software actually works. We call this Software Intelligence. We're now building the bridge that puts it directly in the hands of AI agents.
What You'll Be Building
As Technical Product Manager – AI & Agents, you'll own the product definition and roadmap for integrating CAST's platforms — CAST Imaging and CAST Highlight — into the agentic AI ecosystem. Concretely:
• MCP Server & Agentic integrations. CAST Imaging already exposes its structural insights via an MCP server, making any MCP-aware agent — GitHub Copilot, Claude Code, Gemini — structurally aware of the application it's working on. You'll drive what data gets exposed, how agents consume it, and what new capabilities this unlocks for developers, architects, and transformation teams.
• Hyperscaler partnerships. You'll manage and grow technical integrations with AWS and Google Cloud. Our published research with Google has already demonstrated that augmenting Gemini with CAST's structural analysis produces measurably deeper results on enterprise codebases. You'll be the product owner turning that into a repeatable offering.
• GSI co-innovation. Tier-1 global system integrators are at the forefront of industrializing AI in the software development lifecycle — at enterprise scale, across industries. You'll work directly with them to understand where AI-driven modernization breaks down in practice, what's missing, and where CAST intelligence fills the gap. They're one of your best proxies for real market needs, and a source of product ideas you won't find in analyst reports.
• Next-generation retrieval. Our research team is actively exploring approaches that go beyond standard RAG — combining deterministic structural graphs with semantic retrieval to give agents richer, more grounded context. You'll translate emerging research into product bets, defining what gets productized and when.
What We're Looking For
• Hands-on background in software engineering or architecture. You can read a call graph, understand what a dependency means in practice, and have opinions about technical debt.
• Experience with agentic AI, LLM integrations, or developer tooling — building products or shipping integrations.
• Ability to work across research, engineering, and commercial teams — and translate between all three.
• Fluent English. Our teams and partners are global.
Why This Role
The intersection of software intelligence and AI agents is where the next generation of enterprise software transformation will be decided. You'll work with a research team that publishes with Google Cloud, ships MCP integrations used by real enterprise customers, and is actively pushing the frontier on how AI understands software at scale.
The scope is real. The partners are serious. The problem is unsolved.
Reporting to: Head of R&D
Originally posted on Himalayas