Lead Software Engineer

Role Summary

EGG Digital is looking for a Software Engineering Lead to own end-to-end engineering delivery of our

AI-powered data platform. Reporting to the Head of Data Science & AI Products, you will set the

technical strategy and architecture, lead and grow a high-performing engineering team, and drive

engineering, operational, and delivery excellence across multiple workstreams and vendors. You will

stay hands-on with the code while partnering with product, data science, and enterprise clients to

turn business needs into reliable, scalable systems.

Roles and Responsibilities

• Technical Leadership: Own end-to-end engineering delivery of the platform, from technical

strategy and roadmap through production operations and incident response. Lead, mentor,

and grow a high-performing engineering team, set the hiring bar, run performance and

career development, and build a culture of ownership, craftsmanship, and psychological

safety.

• Architecture and Technical Strategy: Own the system architecture, the build-versus-buy

and technology selection decisions behind it, and a multi-quarter technical roadmap.

Design for scale, reliability, security, and cost of operation, and drive decisions through

written design documents and RFCs reviewed in the open.

• Engineering Excellence: Set and enforce standards for code review, automated testing,

continuous integration and deployment, security, observability, and production support.

Measure and improve delivery health with DORA metrics (deployment frequency, lead time,

change failure rate, time to recovery), and govern the adoption of AI-assisted development

tools.

• Operational Excellence and Reliability: Define service-level objectives and error budgets,

own on-call and incident management, lead blameless post-mortems, drive down toil

through automation and platform investment, and own the cloud cost efficiency of the

systems you run.

• Delivery Management: Translate business requirements into technical plans, estimate and

sequence work across workstreams, manage dependencies and scope trade-offs, and

surface technical risk early with clear options for stakeholders.

• Multi-workstream and Vendor Coordination: Orchestrate delivery across multiple parallel

workstreams and teams, and manage external vendors and technology partners.

• Hands-on Technical Depth: Stay close to the code: review critical changes, prototype high-

risk components, unblock the team on the hardest problems, and act as the final escalation

point on technical decisions.

Cross-functional Collaboration and Client Engagement: Partner with product, design, data

science, and quality functions to keep the solution coherent end to end. Represent

engineering to enterprise clients and executives in business language, and influence

roadmap decisions with data and sound technical judgement.

Qualifications

• Educational Background: Bachelor's or Master's degree in Computer Science, Software

Engineering, or a related field, or equivalent practical experience.

• Experience: A minimum of 10 years in software engineering, including 3+ years leading

engineering teams and owning delivery of a production system end to end in an agile

environment, ideally in a high-scale product or top-tier technology organisation.

• Application Development: Expert-level depth in at least one modern backend stack (e.g. Go,

Python, or TypeScript/Node.js) with strong API design (REST, gRPC), a clear view of

microservices versus monolith trade-offs, and working command of a modern

JavaScript/TypeScript frontend framework such as React.

• Distributed Systems and System Design at Scale: Deep grounding in scalability, reliability,

caching, consistency models, event-driven architecture (Kafka or equivalent), idempotency,

and fault tolerance, with proven experience designing high-traffic systems on large-scale

data where query performance and processing cost are design constraints.

• Data and Infrastructure: Strong SQL and NoSQL data modelling, including schema design

and query optimisation, with hands-on experience across a major cloud platform (AWS,

GCP, or Azure), containers and Kubernetes, infrastructure-as-code (Terraform or equivalent),

and CI/CD pipelines.

• Big Data Platforms: Hands-on experience building or operating large-scale data platforms,

including batch and streaming pipelines, data lake or lakehouse architectures (Spark,

Databricks, or equivalent), distributed processing and storage formats, and data quality and

governance at terabyte scale.

• Reliability, Observability, and Security: Experience running production systems with SLOs,

on-call rotations, and structured incident management; observability across logging,

metrics, and tracing (e.g. OpenTelemetry, Grafana); and security fundamentals including

secure coding (OWASP), identity and secrets management, threat modelling, and data

privacy compliance (PDPA, GDPR).

• Engineering Practices: Git workflows and trunk-based development, automated testing

strategies spanning unit, integration, contract, and end-to-end tests, performance and load

testing, and Agile/Scrum delivery.

• AI-Native Engineering: Experience integrating machine learning models and LLM-based

services into production systems (model serving, retrieval-augmented generation,

evaluation, guardrails, cost and latency management), with practical judgement on where

AI-assisted development tools accelerate teams without eroding quality.

• People Leadership: A proven track record of hiring, coaching, and retaining strong engineers,

running performance reviews and career development, raising the technical bar through

calibrated interviewing, and building inclusive, high-trust teams.

• Communication and Influence: Excellent written and verbal communication, including

design documents and executive-ready updates, conflict resolution, the judgement to know

when to delegate and when to dive in, and the ability to explain technical trade-offs to non-

technical audiences and enterprise clients.

• A Plus: Experience building personalization and recommendation systems, CRM and loyalty

platforms, marketing technology (customer data platforms, campaign orchestration,

marketing automation), or social media and messaging platform integrations (e.g. LINE,

Facebook, TikTok). Experience in telecommunications, location or mobility data, or large-

scale data platform environments is also valued.

About EGG Digital

EGG Digital is more than a technology company... We are growth accelerators.

We believe people are the driving force behind all growth and we blend human and artificial

intelligence to unleash the potential of our people.

We're a team of changemakers, never stopping to explore, experiment and stay actively curious.

EGG Digital is the digital solutions and services company that catalyzes business impact through

the power of human and artificial intelligence.

About our Services

With our offices in Thailand and Malaysia, EGG Digital covers 4 main areas of expertise:

• Media & Communication

• Personalized experience

• AI/ML-Powered Big Data Analytics & Recommendation

• AI/ML-Powered Data Visualization and Actionable Insights

Our wide range of services go from retail & data analytics, insight & media monetization, to being

the Top 2 Line Reseller and more generally a data, media & mobile specialist. We have plenty of

ready to use or customized solution platforms (BI, CRM, SMS...) that enable large corporate clients

and SME to achieve their business goals.