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Principal Product Manager
Company Overview:
Fractal Analytics is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision.
Fractal is focusing on selling world-class suite of vertical and functional AI products that solve high value enterprise problems under the brand Cogentiq.
About (Fractal’s Agentic AI Platform): Cogentiq is Fractal’s secure, scalable, enterprise agentic AI platform that enables teams to build, test, deploy, monitor agents and multi‑agent workflows with strong observability, evaluation, guardrails and RBAC across any cloud or LLM framework. It includes a no/low‑code development console , Agent & MCP Gateways , and an enterprise marketplace for reusable agents, tools, connections and guardrails .
The Mission:
We are looking for a Principal Product Manager to own the roadmap and technical execution of . This isn't a traditional "ivory tower" PM role. You will be the technical architect of our 90-day go-live promise, acting as a bridge between deep AI research and the messy reality of commercial insurance workflows. You will lead the transition from "Black-Box" AI to "Glass-Box" transparency, ensuring our platform doesn't just predict risks but explains them using 120+ validated data points.
The Hands-On Reality (What You’ll Actually Do)
1. "Zero-to-One" Platform Architecture
Technical PRDs: Write high-fidelity specifications for Agentic AI workflows that translate into process automation and decision intelligence. You aren’t just listing "features"; you are defining how data flows from an unstructured PDF or Database into a structured UI/UX to help the User take accurate decisions Glass-Box UX: Work directly with designers to build interfaces that simplify the life of the User while helping them perform at an expert level. You will design how an underwriter "double-clicks" into an AI suggestion or compares current case with portfolio. 2. Forward-Deployed Solutioning
The 48-Hour Configuration: Lead "Bootcamps" where you configure Cogentiq-Underwriting product in front of Chief Underwriting Officers. Learn from the field rather than guess at your desk. API & Integration Mapping: Partner with client IT teams to map Cogentiq input-outputs into legacy systems (Guidewire, Duck Creek). You should be comfortable whiteboarding an API integration or discussing data normalization strategies. 3. Commercial ROI Engineering
The "Combined Ratio" Narrative: Translate technical improvements or system accuracy gains into bottom-line impact. You will build the Economic Value Models that prove how Cogentiq reduces loss ratios and improves productivity. Rapid Prototyping: Use low-code tools or wireframes to test new "intelligence" features with users before they hit the engineering sprint. Who You Are
The Architect-Diplomat: You have 10–12 years of experience. You can debate the nuances of configuration files with engineers at 10:00 AM and present a Business Case to a CXO at 2:00 PM. Insurance Fluent: You don't need a glossary to understand , , or . You understand that for an underwriter, "trust" is more important than "speed." Bias for Action: You prefer a "working prototype" over a 50-slide deck. You are comfortable navigating the ambiguity of a startup where the "best way" hasn't been written yet. Technical Mastery (The "2 out of 5" Rule)
1. AI Orchestration : Deep understanding of LLM prompt engineering , RAG architectures, and the trade-offs between model accuracy and processing latency.
2. Domain Engineering : Deep knowledge of Commercial P&C workflows (Submission → Clearance → Risk Assessment → Quote). You know where the friction lives.
3. Solution Delivery : Experience as a Forward-Deployed Engineer or Technical PM at a high-growth SaaS or Palantir-style deployment model.
4. Growth Strategy : Proven ability to build ROI Calculators and Product-Led Growth (PLG) loops that drive platform adoption in "change-resistant" industries.
5. Platform engineering : Proficiency in Data flow discussions, understanding how to abstract a specific client requirement into an actionable schema.
Qualifications
Educational Background: Bachelor’s degree in a STEM field (Computer Science, Engineering, Mathematics) or a Quantitative field (Economics, Finance) required; MBA or MS in Data Science/AI preferred. Professional Experience: 10–12 years of total experience, with at least 5+ years in Product Management , Technical Product Ownership , or Platform Engineering within a B2B SaaS environment. Domain Expertise: Direct experience in InsurTech, FinTech, or Enterprise AI . A deep understanding of the insurance is highly preferred. AI/ML Implementation: Proven track record of shipping and scaling software or platform products , specifically those involving NLP, document extraction (OCR/IDP), or Large Language Models (LLMs) in a production environment. Technical Literacy: Ability to read API documentation, query databases using SQL , and use tools like Postman to validate technical integrations; sufficient fluency to understand cloud architecture (AWS/Azure) is a plus but not necessary. Strategic Execution: Experience leading client-facing deployments or "Bootcamps," with the ability to translate complex customer requirements into a configurable product roadmap. Systems Familiarity: Prior experience with (or exposure to) core insurance platforms like Guidewire, Duck Creek, or such other core systems is a significant advantage. Product Craft: Expert-level ability to write Technical PRDs that decompose ambiguous AI capabilities into granular logic, data schemas, and "Glass-Box" UI requirements. Commercial Acumen: Strong understanding of SaaS business metrics and the ability to build ROI models that link product features to high-level business outcomes Soft Skills: Exceptional "translator" skills—the ability to command a room of skeptical subject matter experts (Underwriters) while maintaining high credibility with Senior Engineers. Mindset: High-agency, "full-stack" mentality; comfortable operating in the "gray area" of an early-stage startup where you must move from high-level strategy to hands-on configuration daily. Location Preference : Bengaluru
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If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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