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    Job · 21258562

    NOIDA · FULLTIME

    Senior Product Manager - Automated Data Extraction

    Daloopa

    Daloopa

    Noida · onsite · Posted 5d ago

    Sourced fromFoundit
    Not disclosed3–10 yrsfulltimeNoida

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    Section · 01

    About this role

    Location: Noida / Remote

    Department: Product

    About Daloopa

    Daloopa is the leading provider of AI-powered fundamental data for institutional investors. Headquartered in New York, with a growing team in India, Daloopa's proprietary platform sources, structures, and distributes one of the most comprehensive and accurate financial datasets in the market, helping investors accelerate research, financial modeling, and decision-making.

    Trusted by hedge funds, private equity firms, mutual funds, corporates, and investment banks globally, Daloopa recently secured $47 million in Series C funding, bringing total funding to over $100 million. This investment will accelerate the company's mission of powering the next generation of AI-driven financial workflows.

    At Daloopa, we are driven by our values: Obsess over the Customer, Raise the Bar, Be Intensely Proactive, and No BS. Joining us means being part of a high-performance culture where innovation, ownership, and impact go hand in hand.

    Role Overview

    We are looking for a Senior Product Manager for our AI-powered automated extraction platform the core system powering automated extraction as we scale across global coverage.

    This role sits at the intersection of LLM systems, native AI/ML systems, experimentation, and product strategy. You will own the evolution of our native extraction stack, ensuring the platform remains reliable, scalable, and measurable as we expand into new regions, document types, and workflows.

    You will work closely with Engineering, Operations, and Product leadership to improve extraction quality and performance, scale experimentation velocity, and operationalize human-in-the-loop workflows.

    This is a high-ownership role for someone who is deeply technical, highly execution-oriented, and excited about building real-world AI systems at scale.

    Key Responsibilities

    • Own the roadmap for native AI/ML stack for our AI-powered extraction platform, focused on scalability, reliability, and quality.
    • Ensure extraction quality remains reliable and robust as we expand across regions and document types by building strong benchmarking, guardrails, and quality-check systems.
    • Partner with Engineering and AI/ML teams to drive experimentation, optimize routing across ML and LLM systems, and scale successful capabilities into production.
    • Collaborate cross-functionally across Product, Engineering, and Operations to align priorities, execute quickly, and deliver measurable business impact.
    • Stay current on advancements in AI/LLMs and apply emerging capabilities thoughtfully into platform strategy and execution.

    Skills and Qualifications

    We're looking for a highly technical Product Manager with 3+ years of experience building AI/ML product features, or workflow/tooling products, and 8+ years of PM experience at Series B or later companies.

    You'll be a strong fit if you:

    • Have experience owning complex platform or infrastructure products end-to-end.
    • Have worked closely with AI/ML systems, LLM workflows, data pipelines, or automation platforms.
    • Understand the nuances of reliability, observability, experimentation, and evaluation systems for AI products.
    • Can comfortably work with highly technical teams and participate in architecture and system design discussions.
    • Have strong product judgment and can balance speed, quality, scalability, and operational complexity.
    • Are highly analytical and comfortable using data to drive prioritization and decision-making.
    • Have experience designing experimentation frameworks, benchmark evaluations, or feedback loop systems.
    • Possess strong written and verbal communication skills and can simplify complex technical concepts.
    • Thrive in fast-paced, ambiguous environments with high ownership and autonomy.

    Preferred Qualifications

    • Have shipped, as an IC, at least 1 AI-native product or agentic workflow or hybrid ML/LLM system into production at 1K+ DAU or transactions per day scale.
    • Experience in hedge funds, sell-side research, investment banking, or investment management in general is a plus
    • Experience with LLM-powered products, AI agents, or hybrid ML/LLM systems.
    • Familiarity with SQL, experimentation frameworks, and product analytics tools.
    • Experience scaling automation systems across multiple workflows, geographies, or datasets.
    • Background in B2B SaaS, AI infrastructure, or FinTech products.

    Why Join Daloopa

    Impact at scale: Your work directly supports some of the world's most demanding investment teams.

    Culture of excellence: Be part of a team that values accuracy, speed, and raising the bar every day.

    Growth opportunities: Gain exposure to global capital markets while sharpening your financial and analytical skills.

    Dynamic workplace: A culture built on ownership, transparency, and collaboration, where every contribution matters.

    Employee Benefits

    • Comprehensive Health Insurance
    • Employee well-being program with 24x7 medical assistance
    • Work-life balance with flexible policies

    Sourced from foundit

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    Section · 02

    Skills

    benchmark evaluationsfeedback loop systemsLLM WorkflowsAutomation platformsexperimentation frameworksProduct analytics toolsAI/ML SystemsSQLData Pipeline

    Section · Company

    About Daloopa

    Daloopa

    Daloopa

    Software Product

    380

    employees

    2019

    7 years old

    Noida, Uttar Pradesh

    India

    ₹6.3L PA avg

    Avg at Daloopa

    About

    Founded in 2019 and headquartered in New York, with a growing team in Noida (India), Daloopa is on a mission to transform the way investment professionals work.

    Industries

    Software Product

    Employee ratings

    10 reviews

    2.9/ 5

    Culture

    3.3

    Career growth

    2.3

    Work-life

    3.4

    Employees rate it well for

    Work-Life Balance33Company Culture31

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