# (Agentic) Product Manager at Backbase

> Hybrid · India · Unspecified · Product · open. Source: https://alderhq.app/jobs/greenhouse%3Aworkatbackbase%3A8188394 (read 2026-11-04).

## Facts (observed)

- Company: [Backbase](https://alderhq.app/companies/backbase)
- Location text: Hyderabad; Hyderabad
- Where it can be done from (inferred): Hybrid · India (evidence: "Location lists "hyderabad"")
- Posted: 2026-09-09 (55 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/workatbackbase/jobs/8188394
- Skills listed (inferred): LLMs

## Pay and sponsorship

- Posted pay: not posted
- Recognised sponsor (NL): registered as "Backbase B.V." (checked 2026-11-03, [register](https://ind.nl/en/public-register-recognised-sponsors/public-register-regular-labour-and-highly-skilled-migrants))

## Description (the employer's text)

### 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

---
Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aworkatbackbase%3A8188394 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.