I. The Role:

1. We are not looking for a traditional administrator or a coordinator who simply manages backlog tickets. You will join OCB's AI Squad – a small, elite, forward-deployed unit modeled on the Palantir Forward-Deployed Engineer and Navy SEAL operating philosophy. As the Product Owner, you will embed directly inside core business divisions alongside our Senior AI Engineers to find the highest-value problems and ship production-grade AI tools that directly move the bank's numbers.

2. You will own commercial and operational outcomes, not Jira tasks. Your performance is measured against two hard targets:

- Cost-to-Income Ratio (CIR) Improvement: Partnering with divisions like Operations, Risk, and AML to map manual workflows and design agentic RAG and document–intelligence pipelines that automate high-cost processes. The goal is to maximize baseline capability using the same headcount.

- Revenue Growth through Personalization: Designing the business logic for personalized engines that lift products per customer, cross-sell conversion, and CASA balances by delivering the right offer to the right customer at the right time.

- You will deeply understand each business division, translate user friction into clear technical objectives, and manage the execution lifecycle to safely integrate AI agents into production systems.

II. What You'll Own:

1. Forward–Deployed Discovery & Delivery:

- Direct Embedding: Sit directly with operators across Retail, SME, Risk, Operations, and AML to document end-to-end workflows and pinpoint exactly where AI can strip out costs or trigger new revenue lines.

- Problem Framing: Translate messy business problems into clean data and orchestration requirements that our AI Engineers can build against.

- Production Deployment: Take ultimate accountability for change management, user adoption, and the realized commercial metric rather than just delivering a software tool.

2. Personalization & Revenue Product Management:

- Agentic Workflows: Shape the customer signals, product-holding profiles, and transaction patterns into specific automated logic for next-best-offer and next-best-action engines.

- Front-Line Enablement: Ensure the output of these engines integrates smoothly with RM/PRM coaching assistants and front–line staff tools, telling them precisely what to pitch to whom.

3. Cost & Operations Automation:

- Automation Prioritization: Evaluate and stack-rank manual business workflows for automation, focusing on areas like credit-policy lookup, risk-analysis support, and AML alert triage.

- Document-Intelligence Scope: Scope out business requirements for data extraction and OCR tools across contracts, collateral, valuation support, and signature verification.

4. Stakeholder Alignment & Core Integration:

- Systems Integration: Partner with IT and Infrastructure leads to ensure our AI products cleanly interface with core banking infrastructure, including T24, Way4, LOS, and OMNI.

- Guardrails & Governance: Collaborate with risk and compliance teams to ensure all shipped tools meet banking-grade data privacy, safety, and observability standards.

III. Technology – Context for Collaboration:

While you will not write code, you must speak the same language as our technical squad. Our squad relies on a deliberate, standardized platform rather than a fragmented ecosystem of tools. You will collaborate daily with engineers building on the following core architecture:

- Agent / Orchestration: LangChain and LangGraph (Our firm, non–negotiable core platform)

- Data Platform: Databricks (Delta Lake, MLflow) and feature stores

- Retrieval & Document AI: Advanced RAG, Vector DBs, Vision-Language Models, and OCR pipelines

1. Experience:

- Proven Track Record: At least 5 years of product management or product ownership experience, specifically launching data-driven products or software systems with demonstrable business impact.

- Regulated Environments: Experience working within banking, financial services, or highly regulated, security-sensitive industries is a strong advantage.

- AI Exposure: Prior experience managing products that leverage machine learning, natural language processing, or LLM-based architectures is highly valued.

2. Core Skills:

- Business Architecture: Ability to break down complex manual operations into clear functional steps, logical decision trees, and data flows.

- Technical Literacy: Comfortable discussing APIs, core integration challenges, RAG pipelines, and data models without getting lost in the details.

- Stakeholder Synthesis: Exceptional ability to align senior business executives, risk officers, and technical engineers around a single execution roadmap.

3. How You Operate:

- Outcome-Obsessed: You measure your success in CIR basis points and revenue lift, not by how many features you release.

- Embedded and Fearless: You are completely comfortable sitting directly with line operators, learning a complex domain from scratch, and presenting hard truths to leadership.

- Bias to Ship: You prioritize getting an imperfect but highly useful tool into production for fast iteration and tight feedback loops over waiting for a perfect theoretical design.

- Bilingual Communication: Strong communication skills to translate highly technical concepts for non–technical stakeholders. Professional fluency in both Vietnamese and English is highly preferred.

4. How We Measure Success (First 12 Months):

- Production Launch: Successfully launch and drive deep adoption of production AI systems inside at least 2 business divisions.

- Measurable CIR Reduction: Deliver verified cost improvements through the automation of manual workflows under your purview.

- Measurable Revenue Lift: Prove clear topline value via increased penetration, higher campaign conversion, or cross-sell lift driven by personalization systems.