AI Engineer

• I. The Role ** This is not a research role and not a "PoC factory." 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: a few exceptional engineers who embed directly inside business divisions, find the highest-value problems, and ship production AI that moves the bank's numbers. ** You will own outcomes, not tickets.
• Your work is measured against two hard targets: - Cost-to-Income Ratio (CIR) improvement — automating high-cost manual workflows (document processing, credit operations, AML/ops review, RM support) so the bank does more with the same headcount.
• Or: Revenue growth through personalization — building AI systems that lift products-per-customer, card and lending penetration, CASA, and campaign conversion by delivering the right offer to the right customer at the right time. - You embed with a division, learn its workflow better than it knows itself, build the agent or pipeline that removes the cost or unlocks the revenue, and put it into production.
• Then you do it again.
• II. What You'll Own

1. Forward-Deployed Delivery

• Embed directly with a business division (Retail, SME, Risk, Operations, AML) — sit with the operators, map the workflow end-to-end, and identify where AI removes cost or creates revenue.
• Own the full lifecycle of each solution: problem framing, architecture, data pipeline, build, deployment, integration with core banking, and the business result.
• You are accountable for the metric, not just the model.
• Ship fast and iterate in production.
• We measure success in deployed systems and basis points of CIR, not slide decks.

2. Personalization & Revenue Engines

• Build AI systems that drive revenue through personalization: next-best-offer and next-best-action engines, pre-approved credit and lending journeys, CASA/cash-leakage retention prompts, and RM/PRM coaching assistants that tell front-line staff exactly what to pitch to whom.
• Connect customer behavioral signals, product-holding data, and transaction patterns into agentic workflows that act — not dashboards that observe.

3. Cost & Operations Automation (CIR)

• Build agentic and RAG workflows that collapse manual cost: credit-policy lookup, risk-analysis support, AML alert triage and case automation, and operations/RM assistant tools.
• Build document-intelligence pipelines — OCR and data extraction for contracts and collateral, valuation support, signature verification, and automated document classification — using vision-language models where they earn their place.

4. Production AI Engineering

• Stand up evaluation frameworks, guardrails, and observability for every system you ship.
• Banking-grade means measurable, monitored, and safe by default.
• Own deployment, model serving, monitoring, and retraining.
• Meet SLAs.
• Partner with IT and infra to integrate cleanly with core banking systems (T24, Way4, LOS, OMNI) and internal platforms.

5. Squad Leadership

• Set the engineering bar. Mentor junior squad members and pull business stakeholders along with you — translating workflow pain into shipped systems and shipped systems into business value.

• Experience: - 4+ years in AI/ML engineering with a real track record of production systems, not prototypes.
• You can point to things running in production with users and business impact behind them. - Banking, financial services, or another regulated, security-sensitive industry is a strong plus. - Bonus: experience as a forward-deployed / solutions / embedded engineer where you owned a customer or business outcome directly.
• Core Skills: - Production-grade LangChain/LangGraph — multi-agent architectures, function calling, tool integration, stateful graphs.
• This is the bar. - Strong command of advanced RAG pipeline design and agent orchestration. - Computer Vision / VLM for OCR, document intelligence, and image analysis. - LLMOps/MLOps: model serving (FastAPI, vLLM, Triton), containerization (Docker, Kubernetes), CI/CD, evaluation and guardrails. - Databricks (Delta Lake, MLflow) for data processing and scaled deployment.
• How You Operate: - Outcome-obsessed.
• You measure your work in CIR basis points and revenue lift, not commits. - Embedded and fearless.
• Comfortable sitting with operators, learning a domain cold, and owning the result in front of business leaders. - Bias to ship.
• Production over PowerPoint.
• Fast iteration, tight feedback loops. - Excellent communicator who can translate technical work for non-technical stakeholders.
• Bilingual Vietnamese/English is a strong plus.