---
title: '(Agentic) Product Manager at Backbase'
canonical: 'https://feeny.ai/job/agentic-product-manager-backbase-hyderabad-6ynk2292qc4q'
type: 'job'
last_seen: '2026-09-12'
---

# (Agentic) Product Manager at Backbase

- **Company:** Backbase
- **Location:** Hyderabad, India
- **Posted:** 2026-09-09
- **Last confirmed live:** 2026-09-12
- **Apply:** https://job-boards.greenhouse.io/workatbackbase/jobs/8188394

## Job description

## About This Role

We are building an agentic banking platform for large enterprise banks. Multi-modal AI converts business intent into autonomous agents that orchestrate processes, integrate data, and make intelligent decisions — turning weeks of manual work into hours.

You will lead AI agents and intelligent automation — building capabilities that deploy autonomous agents to solve complex banking problems at enterprise scale. This is not a pillar-specific role. You'll work across three interconnected pillars (Durable Processes, Data Connectors, AI Agents), collaborating with peer PMs to architect and ship agentic solutions end-to-end.

You'll report directly to the Product Director and own the complete journey: from defining what agentic capabilities matter most, to shipping them, to measuring their impact. This role is for a PM who understands how AI agents fundamentally change enterprise automation, who can navigate technical and business complexity, and who ships with both ambition and rigor.

## What You'll Own

Strategic ownership

- Define the AI capability roadmap — which features move the needle, which delight customers, which drive competitive advantage
- Make the hard calls: what ships in Year 1, what comes after, what's out of scope
- Own the quality bar — "enterprise grade" means reliable, explainable, compliant, and safe. Set and enforce that standard.
- Shape how AI surfaces across the platform — consistency in UX, tone, and behavior across copilot, solution builder, and other capabilities

Execution leadership

- Lead cross-pillar alignment — work with peer PMs to define integration points and success metrics
- Conduct customer discovery: what AI capabilities matter most, what fears do they have about AI, what use cases are most valuable
- Make data-driven decisions: usage patterns, LLM cost, inference latency, customer sentiment all inform roadmap
- Unblock ambiguity: when technical feasibility isn't clear (cost, latency, quality), you synthesize information and move forward decisively

Partnership with platform PMs

- Collaborate with peer PMs who own the platform pillars
- Establish clear integration contracts: where AI surfaces in their UIs, how data flows from their features to your LLM calls, how they measure success

We're Looking For

Experience shipping one or more of the following:

AI-native products or features that users love · Enterprise software with AI capabilities built in (not tacked on) · Products that required deep LLM integration and cost optimization · Cross-functional initiatives that span multiple teams or product areas · Experiences that balance power with usability.

Core capabilities

- AI fluency, not just enthusiasm – You understand LLM capabilities and limits. You know the difference between a prototype and a production system. You think about cost, latency, hallucination, and compliance from day one.
- Systems thinking across pillars – You see how an AI feature in one pillar impacts the others. You optimize for platform coherence, not local feature wins.
- Customer reality grounding – You spend time with users and understand their AI skepticism. You don't oversell; you deliver reliably.
- Quality obsession – You know that "enterprise grade" is non-negotiable. Explainability, compliance, reliability, and safety are as important as feature velocity.
- Technical depth without being an engineer – You read research, understand prompt engineering tradeoffs, can discuss model selection and fine-tuning. You think rigorously about technical problems.

## Nice to have

- Shipped copilot or AI-assisted features in a production SaaS product
- Experience with LLM cost optimization, latency budgeting, or inference infrastructure
- Familiarity with enterprise workflow, process automation, or BPM domains
- Track record of shipping cross-functional initiatives with competing stakeholders

## About Backbase

## Company Overview
- **One-liner**: Backbase builds the AI-native Banking OS that unifies digital channels, front office, and operations so banks can coordinate customers, employees, and AI agents from one platform.
- **Entity Type**: Private (no public ticker; no funding rounds disclosed – appears organically grown)
- **Headquarters**: Amsterdam, Netherlands
- **Founded**: 2003
- **Founders**: Not publicly available (described as “founder-led” but names not stated on the provided sources)

## Core Business
- **Primary industry**: Banking technology / financial services software
- **Target customers**: B2B – large banking institutions (120+ banks globally, serving 75M+ daily users)
- **Mission/purpose**: “We built something that didn't exist before – an AI-native Banking OS where humans and AI agents work side by side, at scale, inside real banks.”

## Products & Services
- **AI-native Banking OS**: A unified platform that sits above legacy cores, CRMs, and data platforms. It orchestrates customer engagement (digital banking, conversational banking, front-office workspaces) and banking operations (high-volume processes like disputes, payments, lending). Designed to be deployed incrementally without rip-and-replace. Includes native AI agents for governance, automation, and auditability.

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: 2,000+ employees globally, 50% of team in R&D, 120+ banks as customers, 75M+ active daily users across the platform
- **Notable Investors/Partners**: Not publicly available
- **Growth Signals**: Expanding globally with 16 offices across 5 continents; notable customer examples include I&M Bank (Africa) which grew onboarding from 2,000 to 21,000 new customers per month, and Techcombank (Vietnam) achieving 50% of savings and investments through digital. The company is actively hiring and describes itself as “in the middle of the biggest shift in banking’s history.”

## Competitive Advantages
- **Unified Frontline architecture** – breaks down fragmentation between digital channels, front office, and operations, enabling banks to move fast without sacrificing compliance or security
- **AI-native from the ground up** – not a bolt-on; full governance and audit trails for every AI decision
- **Progressive modernization** – works with existing cores, no big-bang migration required
- **18+ years of banking domain expertise** (since 2003) with a singular focus on banking since 2012

## Strategic Focus
- Deepening AI integration into banking workflows (Elastic Operations – scaling throughput without scaling headcount)
- Expanding global footprint (17 offices, including recent additions in Hyderabad, Riyadh, Mexico City, and Toronto)
- Continuing to shift banks from legacy fragmentation to a unified, composable operating system

## Why Work Here
- **Culture**: Described as “ambition without ego,” “bias for action,” “you own what you ship,” and “the work is the standard.” Flat structure with no micromanagement.
- **Work model**: Hybrid – “Where you do your best work is up to you.” Offices in 17 locations globally.
- **Perks**: Annual learning budget, global exposure, wellness support, real ownership of projects from day one.
- **Engineering focus**: 50% of the team in R&D; real AI running in production, not just pilots.

## Sources
1. [backbase.com/careers](https://www.backbase.com/careers)
2. [backbase.com/about](https://www.backbase.com/about)
3. [backbase.com](https://www.backbase.com/)
4. [linkedin.com/company/backbase](https://www.linkedin.com/company/backbase)

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