Tech Lead (Socom)

Who we are

Intrepid Asia is a leading e-commerce and Digital Solutions Provider in Southeast Asia. We offer end-to-end omni-channel ecommerce management, Livestreaming, Video production & Affiliate Management for Social Commerce, plus full funnel Digital Marketing Services and advanced Market Intelligence, all powered by state of the art in-house Technology to our client base of leading international brands across all key marketplaces and social platforms in all 6 SEA countries. Brands love our regional presence, our excellent data-driven and growth-focused services, which are enabled by the strongest team in the industry, and our advanced marketing and tech capabilities.

We are growing rapidly and as the exclusive partner of Flywheel in SEA, we offer many exciting opportunities to work with leading brands across multiple categories and key industry players. By joining us, you will work on the cutting edge of digital and social commerce in SEA, and experience what it takes to drive a successful e-commerce business end-to-end.

The team you will be part of

Our Tech Team is the engine behind our digital capabilities — designing and building the platforms, tools, and systems that power our services across the eCommerce ecosystem. From automation to optimization to data integration, the team turns complex challenges into seamless solutions, enabling scale, speed, and smarter decision-making. With innovation at its core, Tech drives the digital backbone of our business and empowers every function to perform at its best.

The team operates across multiple product domains — MarTech, Data-as-a-Service, and Social Commerce — each with its own suite of internal tools and external-facing applications. All products are built on a common shared infrastructure and benefit from a collaborative engineering culture where knowledge-sharing, code standards, and continuous learning are central to how we work.

The part you will play

As Tech Lead, you will own the end-to-end engineering of Intrepid's Social Commerce product suite — a set of AI-powered tools that help brands, marketers, and content teams operate more effectively across TikTok, Shopee, Lazada, Meta, Google and other key SEA platforms.

You will be building two major product verticals from scratch:

Social Commerce Intelligence Platform

A data-driven performance management app for brands to track, analyse, and act on their affiliate marketing programs, creator partnerships, and livestream commerce operations. Users can monitor creator GMV, commission performance, live traffic, conversion rates, and content ROI — all in one place — and get actionable insights to make faster, better decisions on campaign allocation, creator selection, and live scheduling.

AI Video Automation Platform

An end-to-end AI creative production platform — purpose-built for social commerce content in SEA. Users input a product brief and reference images; the platform generates scripts, builds a scene-by-scene storyboard, pre-generates model visuals and backgrounds (ensuring visual consistency), produces per-scene video clips, adds voiceover and subtitles, and delivers a ready-to-publish video. The platform supports both a guided Review Mode (step-by-step human approval and editing at each stage) and a Turbo Mode (fully automated, one-click end-to-end). All AI model selections, prompt templates, and creative parameters are configurable by users — no developer changes required.

Both products integrate with our shared platform: authenticate via AWS Cognito JWT, call ShareFoundation APIs for user ACL and subscription entitlements. Self-serve analytics and embedded BI dashboards (Apache Superset, Cube, Starrock, BigQuery) are key components of both products. You will make the foundational technical decisions and lead a team of engineers to deliver these products to brand clients across 6 SEA markets.

As a Tech Lead, you will take charge of

Technical Architecture & Engineering

• Architect both product backends from scratch: Golang microservices, RabbitMQ-based event-driven pipelines, async job workers, and AI/LLM integration layers.
• Design pluggable AI model adapter layer: strategy pattern to add or swap providers (LLM, image gen, video gen, TTS, ASR) without pipeline code changes — configurable per user session.
• Define data architecture: MySQL schemas, Redis caching, S3/MinIO storage, and data access patterns to and from the analytics layer (BigQuery, StarRocks).
• Design the Superset embed integration: secure guest token flow, tenant-scoped dashboards, row-level security, and custom self-serve dashboard builder on top of Cube (semantic layer).
• Integrate with ShareFoundation SSO: validate AWS Cognito JWT tokens, consume ShareFoundation ACL APIs to enforce feature access and subscription entitlements.
• Build and own CI/CD pipelines, Kubernetes deployments, and observability stack (structured logging, Prometheus/Grafana, distributed tracing, AI API cost tracking).

Team Leadership & People Development

• Lead, mentor, and grow a team of backend and frontend engineers — setting clear technical direction, reviewing code and designs, and actively unblocking delivery.
• Build and maintain a strong engineering culture: define coding standards, TDD practices, code review norms, and architectural decision records (ADRs) that the whole team follows.
• Run regular knowledge-sharing sessions, tech talks, and internal training to upskill the team — including how to effectively use AI-assisted development tools (Cursor, Claude, Windsurf, etc.) to improve engineering velocity.
• Stay current with the AI, LLM, and social commerce technology landscape — proactively evaluate new models and tools, and bring relevant recommendations to the team and product roadmap.
• Foster a culture where AI is embedded into daily engineering workflows: code generation, test writing, debugging, documentation, and code review assistance.

Cross-Team Collaboration & Stakeholder Management

• Work closely with the Product team to translate business requirements into clear technical specifications — challenge assumptions, propose alternatives, and align on delivery scope and timelines.
• Collaborate with other engineering teams (MarTech, DaaS, Data Engineering) on shared platform decisions, API contracts, and data pipeline dependencies.
• Partner with the Business Intelligence and Data teams on analytics data models, dashboard requirements, and self-serve analytics features.
• Communicate technical trade-offs, risks, and progress clearly to non-technical stakeholders — adapt depth and framing depending on the audience.