Engineering leader with 9+ years building data platforms, GenAI systems, and the teams that run them. Currently Director of GenAI Software Engineering at Standard Chartered, leading a squad delivering RAG pipelines and agentic workflows inside one of Asia’s most regulated institutions. I tend to care as much about how things get shipped as what gets shipped — the process, the culture, the constraints that nobody warned you about.
What I Do #
I sit somewhere at the intersection of data engineering, GenAI systems, and engineering leadership. Over the years that’s meant writing a lot of Python, designing a lot of pipelines, and more recently spending a meaningful chunk of time on things like how to get an agentic workflow past a compliance review, or how to grow an engineer who’s never had a 1:1 before.
My technical home is data — lakehouses, pipelines, transformations, the full stack from raw ingestion to analytical surface. The last couple of years have pulled me toward GenAI infrastructure: RAG, vector databases, LLM orchestration, and the newer question of how you build reliable agentic systems that actually hold up in production.
On the leadership side I’ve built teams from scratch (3 to 11 engineers at ADI), run pre-sales architecture discussions, designed delivery SOPs, and spent a lot of time just trying to make sure people have what they need to do their best work.
Experience #
Director, GenAI Software Engineering · Standard Chartered Singapore Dec 2025 – Present
Leading Team Vectors — a 9-person squad building GenAI-powered data solutions inside a global bank. The technical work covers RAG pipelines, vector-database preparation, and durable agentic workflows via Temporal.io, deployed across both on-prem and Databricks cloud environments.
What makes this interesting (and occasionally difficult) is the gap between what’s architecturally elegant and what can realistically reach production given data security boundaries, governance approval paths, and shared infrastructure at varying maturity levels. A lot of my job is navigating that gap without losing momentum — or relationships.
Also mandated and operationalised AI-assisted coding across the team in a compliance-compatible way. The team has fully transitioned to spec-driven development and agentic engineering practices. Built and open-sourced agentic-beacon as part of that culture work.
Data Engineering Lead (Consultant) · Asian Development Bank Jun 2025 – Nov 2025
Technical lead on ADB’s GenAI data platform, with a team of 4. The flagship deliverable was a RAG application over a 200,000+ document knowledge base covering multilateral development research and policy content, with daily ingestion growth.
Adapted an architecture previously battle-tested in commercial engagements (Airflow, Databricks, MLFlow, Terraform) to ADB’s requirements as a multilateral institution. Also contributed to architectural design of ADB’s new credit analysis platform before the engagement concluded.
Head, Data Engineering · Aboitiz Data Innovation (ADI) Apr 2024 – Jun 2025
Expanded scope to pre-sales technical leadership alongside running the engineering function. Attended pre-sales meetings as the senior technical voice, providing architecture estimates and the kind of credibility that helps close contracts.
Grew the function to 11 engineers across three teams: MLE delivery, DE delivery, and an internal platform/infra/products team.
Lead, Data Engineering · Aboitiz Data Innovation (ADI) Feb 2023 – Apr 2024
Scaled a 3-person team to 10 in 12 months, while simultaneously delivering commercial data projects and building reusable internal products. The headline product was a white-label Data Platform — fully Terraformed, reproducible across AWS and Azure, with configurable security and data boundaries per client.
Standardised delivery lifecycles for both DE and MLE engagements: SOPs, scoping templates, handoff workflows. The kind of work that’s invisible when it’s done well.
Pod Lead, Data Platform · Xendit Sep 2021 – Jan 2023
Led the self-serve data platform pod at a high-growth fintech. Maintained a 1.5 PB lakehouse serving ~300 internal consumers, oversaw 1,500+ batch and 30+ streaming pipelines, and drove the Delta Lake migration from a Parquet-based lake.
Designed a YAML-based centralised pipeline configuration repo integrated with Airflow — making pipeline additions and removals fully self-serviceable. Introduced semantic versioning, end-to-end test frameworks, poetry, and Airflow 2 in distributed setup.
Data Team Lead · Real Estate Analytics (8prop) May 2020 – Sep 2021
Built the full data stack from scratch for a proptech startup across SG, MY, and HK — Airflow + dbt scheduler, a distributed web crawler ingesting 50+ data sources, and 60+ entity models in Postgres. Team of 5 covering all data engineering, ops, and analytics.
Data Engineer · Healint Aug 2018 – May 2020
Full-stack data engineering in health-tech. Migrated a legacy Postgres warehouse to Redshift, built and maintained ~40 Airflow batch DAGs and 2 streaming pipelines, and shipped 4 microservices end-to-end including 2 data science products. First real taste of owning the full lifecycle from infra to production.
Data Engineer · Aly Pte. Ltd. (Spiking) Jul 2017 – Apr 2018
First proper engineering job. ETL pipelines, database optimisation, and a self-learning NLP keyword extractor for stock news. Learned a lot about what good (and bad) data infrastructure looks like by inheriting some of each.
Tech I’ve Worked With #
AI / GenAI — RAG architecture, vector databases, LLM orchestration, MLFlow, Temporal.io, embedding pipelines, agentic engineering, spec-driven development
Data Engineering — Apache Spark, Airflow, dbt, Kafka, Delta Lake, Trino, Hive, Databricks, Redshift, Postgres
Cloud & Infra — AWS (Fargate, Redshift, S3, Kinesis, EC2, ELB, VPC), Azure, Terraform, Kubernetes, Docker, CI/CD
Backend — Python, SQL, microservices, REST APIs, FastAPI, SQLAlchemy, event-driven architecture
Education #
Bachelor of Science, Business Analytics · National University of Singapore, School of Computing 2014 – 2018 · Science & Technology Scholarship
Elsewhere #
You should only notice me when something is broken — but if you want to reach out, GitHub is the best place to find me.