---
title: 'Senior Product Manager at Metaforms'
canonical: 'https://feeny.ai/job/senior-product-manager-metaforms-bengaluru-683dp4187sen'
type: 'job'
last_seen: '2026-10-14'
---

# Senior Product Manager at Metaforms

- **Company:** Metaforms
- **Location:** Bengaluru, India
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-09-30
- **Last confirmed live:** 2026-10-14
- **Apply:** https://jobs.ashbyhq.com/metaforms/d6406949-6a4b-44b0-af33-cefdf02afc72

## Job description

## About Metaforms

Metaforms is a vertically integrated AI SaaS platform for market research agencies around the world. The platform helps agencies improve speed, consistency, and delivery quality across research workflows that have historically depended on repetitive manual effort and hard-to-scale specialist knowledge. The product surface is unusual. Surveys behave like programs, business workflows contain hidden operational nuance, and a small mistake can create real downstream cost for an agency and its clients. That means product thinking here is not about copying familiar SaaS patterns. It is about understanding how work is actually done, identifying where AI agents can reliably help, and shaping systems that feel intuitive to users while introducing genuinely new workflows underneath.

## The Role

Metaforms is hiring a Senior Product Manager to define and ship new AI-native products and workflow experiences for research operations. This role sits at the intersection of user discovery, domain synthesis, product design, and engineering execution. The right person is comfortable going end to end, from interviewing users and subject matter experts, to identifying operational bottlenecks, to translating business needs into concrete product requirements, to partnering closely with engineering through delivery. This is a high-ownership role for someone who likes ambiguous spaces, can reason from first principles, and can build from zero rather than relying on existing category templates.

## What You'll Own

User Discovery and Problem Definition

- Conduct frequent user interviews with market research operators, project managers, programmers, and agency leaders to understand how work actually happens.
- Turn messy qualitative input into clear product insights, problem statements, and opportunity areas.
- Work closely with subject matter experts to separate surface requests from deeper workflow or systems problems.
- Build conviction on where AI agents can remove manual effort, improve turnaround time, or increase quality without disrupting critical trust points.

Product Design and 0 to 1 Development

- Define new product concepts, workflow patterns, and operating models for AI-assisted research work.
- Design familiar-feeling user journeys that introduce new capabilities without overwhelming users.
- Write product requirements that are specific enough for engineering to execute, while preserving room for iteration where the solution space is still emerging.
- Iterate rapidly on prototypes, internal feedback, and early customer usage to converge on products that are both useful and operationally viable.

Cross-Functional Execution

- Translate business requirements into clear engineering asks, including scope, constraints, acceptance criteria, and edge cases.
- Partner tightly with engineering, design, operations, and domain experts throughout the build cycle.
- Drive prioritization decisions by balancing customer value, technical feasibility, reliability risk, and speed.
- Ensure the team is solving the right problem, not just shipping the fastest version of the first idea.

Product Quality and Adoption

- Define what good looks like for product outcomes, user trust, and workflow adoption.
- Identify failure modes in user flows, handoffs, and agent behavior, especially in high-consequence operational steps.
- Close the loop between shipped behavior, customer feedback, and roadmap decisions.
- Own rollout, onboarding, and change-management plans with customer success and operators so new workflows land in real agency production including how we measure adoption and efficiency gains.

## What We're Looking For

Must Have

- Product management experience with a strong track record of shipping software products from concept to launch.
- Demonstrated ability to operate in ambiguous, early-stage, or zero-to-one product environments.
- Gone beyond prompting with AI. At work or on the side, you’ve built a prototype, automated a workflow, or shipped a feature using LLMs, APIs, or agents, and can speak to the trade-offs you ran into.
- Strong user discovery skills, including conducting interviews, extracting patterns, and synthesizing findings into product direction.
- Comfort working deeply with subject matter experts and operational stakeholders in domains that are initially unfamiliar.
- Ability to translate business context and user pain points into clear requirements for engineering teams.
- Strong product judgment across scope, workflow design, trade-offs, and iterative delivery.
- Comfort owning the end-to-end journey of how a product should be defined, shaped, and built.
- Excellent written and verbal communication, especially in cross-functional settings where clarity matters more than volume.
- Comfort going deep enough with engineering to write requirements that can be executed without a translator, including constraints, edge cases, and failure modes.
- Willingness to reason about AI/agent behavior in production: when to trust automation, when to require human review, and how quality/reliability show up for users.
- Bias toward defining and tracking workflow outcomes (speed, quality, trust/adoption), not only shipped scope.
- Direct, high-ownership communication under incomplete information clarity over polish, and willingness to call out when process or product direction is wrong.

How Success Looks

- Users say the product fits how their work actually happens, not how software teams assumed it happened.
- Engineering has clear, high-signal product inputs and can move quickly without repeated ambiguity tax.
- New workflows feel intuitive enough to adopt, while still delivering meaningful gains in speed, quality, or operational leverage.
- Product decisions reflect a strong understanding of both customer outcomes and the realities of production systems.
- Shipped workflows show measurable gains in turnaround, quality, or adoption, with clear failure modes understood and managed not just features launched.

## Why Metaforms

- Work on AI products that operate in real production environments, not demos or feature theater.
- Shape entirely new workflow categories instead of incrementally copying existing tools.
- Join a team where product, engineering, and domain understanding are tightly coupled.
- Operate with high ownership, fast iteration loops, and direct influence on what gets built.

## About Metaforms

## Company Overview
- **One-liner**: Metaforms provides an AI-powered platform that automates and augments market research operations for agencies, covering survey programming, data processing, bidding, sample management, and voice research.
- **Entity Type**: Private (Series A)
- **Headquarters**: New York, New York, United States
- **Founded**: 2023
- **Founders**: Akshat Tyagi (CEO), Arjun S (CTO)

## Core Business
- **Primary industry**: Market Research Technology (Market Research Operations / AI for Research)
- **Target customers**: B2B — Market research agencies, insights teams, and survey programmers
- **Mission or purpose statement**: "Making research accessible to every business" by giving market research agencies AI superpowers to deliver insights 10x faster.

## Products & Services
- **Survey Programming (AI-Copilot)**: An AI agent that generates production-ready survey code (SPSS, Dimensions, Python, JavaScript) from uploaded questionnaires. Handles complex logic like MaxDiff, segmentation, piping, and loops. Includes version control, multi-programmer workflows, and real-time error detection.
- **Data Processing**: AI that flags discrepancies, handles complex validation logic, and integrates with existing macros and workflows to automate data cleaning and processing.
- **Bidding Management**: Transforms incoming client emails/RFPs into structured project specifications, identifies missing requirements, and generates accurate quotes using the agency's exact pricing logic.
- **Sample Management**: Automatically routes sample requests to the best suppliers, tracks and re-balances quotas across vendors in real-time, and consolidates responses into cost/feasibility comparisons.
- **Voice Research**: AI-moderated voice interviews at scale, automating scheduling, respondent screening, and data capture, delivering structured insights.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Raised $9 Million in Series A funding (announced 2025)
- **Notable Investors/Partners**: Not publicly named in available sources; investors are listed as part of the Series A round.
- **Growth Signals**: 58 employees as of mid-2025; offices in New York (HQ), Bengaluru, and San Francisco; trusted by "world's leading agencies"; growing team with open roles in product engineering, customer success, and product management.

## Competitive Advantages
- **Vertical-Specific AI**: Unlike general-purpose AI tools, Metaforms is purpose-built for the market research industry, learning agency-specific coding styles, standards, and pricing logic.
- **End-to-End Workflow Coverage**: The platform spans the entire research operations lifecycle—from RFP response and bidding, through survey programming and data processing, to sample management and voice interviews—creating a deep moat.
- **Enterprise-Grade Security**: SOC 2 Type II certified, GDPR compliant, and offers custom security documentation for enterprise clients. Explicitly states no training on customer data.
- **Pattern Learning**: AI adapts to each agency's coding style and preferences in real-time, making it stickier and harder to replace.

## Strategic Focus
- **Product Expansion**: Continuing to build out AI agents across all research workflows (bidding, programming, data processing, sample management, voice).
- **Enterprise Sales**: Deepening integrations with Salesforce and major PM tools, and offering API/email-based workflows to fit existing processes.
- **Scaling the Team**: Actively hiring across product engineering, customer success, and product management to support growth.
- **Market Penetration**: Targeting traditional market research agencies that are constrained by manual processes, enabling them to take on more clients and projects.

## Why Work Here
- **Culture**: Mission-driven team focused on making research accessible to every business. Described as a place where "every business decision should be informed."
- **Work Policy**: Hybrid and in-office roles available depending on location and function. Offices in New York (HQ), Bengaluru, and San Francisco.
- **Team & Growth**: 58 employees and growing. Early-stage startup environment with the opportunity to shape the product and culture.
- **Engineering Culture**: Emphasis on building AI agents that "get your business." Roles like Senior Product Engineer and Senior Product Manager are currently open.
- **Perks**: Not explicitly detailed, but the company highlights 24/7 support for clients and a "build the future with us" ethos.

## Sources
1. [metaforms.ai](https://www.metaforms.ai/)
2. [metaforms.ai/about](https://www.metaforms.ai/about)
3. [linkedin.com/company/metaformsai](https://www.linkedin.com/company/metaformsai)
4. [builtin.com/company/metaforms](https://builtin.com/company/metaforms)
5. [jobs.ashbyhq.com/metaforms](https://jobs.ashbyhq.com/metaforms)

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