Registration of Interest for #AIDA Talent Acceleration Day (Sept 2026) -Senior AI Harness Engineer (Singapore)
Software Engineering, People & HR, Data Science
Singapore
Build AI. Unlock BIG Possibilities with Singtel.
Singtel’s Artificial Intelligence & Data Analytics team, AIDA, is growing its team of AI, data and cybersecurity and technology professionals.
We are inviting experienced AI Harness Engineer to register their interest in current and upcoming opportunities.
Role Summary
At Singtel, we are building AI capabilities across customer experience, network and service operations, enterprise solutions and internal productivity.
As a Lead AI Harness Engineer, you will define and build the engineering foundations around AI models and agents that enable them to operate reliably, safely and at enterprise scale.
You will lead the design of reusable orchestration, context, memory, tool integration, evaluation, simulation, guardrail and instrumentation capabilities that allow AI systems to interact securely with Singtel's data, knowledge, APIs and operational systems.
This is a senior individual-contributor role combining deep hands-on engineering with technical leadership. You will solve complex cross-cutting engineering problems, establish reusable patterns and standards, and shape how production AI systems are engineered across Singtel.
Roles & Responsibilities
- Define the architecture and technical direction for reusable AI harness capabilities across Singtel.
- Design and build common frameworks for agent orchestration, context engineering, memory, tool integration, evaluation, simulation, instrumentation and runtime controls.
- Establish engineering patterns for connecting AI agents securely to enterprise data, APIs, MCP servers, workflows and operational systems.
- Define evaluation strategies and quality gates covering task success, grounding, tool execution, safety, reliability, latency and cost.
- Design scalable evaluation and experimentation infrastructure supporting automated regression testing, simulation, replay and production feedback loops.
- Establish instrumentation and observability patterns that enable teams to understand and diagnose AI and agent behaviour end to end.
- Design mechanisms to capture production failures, user feedback and operational outcomes and convert them into continuously improving evaluation datasets and tests.
- Define patterns for agent identity, permissions, policy enforcement, human oversight, graceful degradation and fail-safe behaviour.
- Build reusable SDKs, libraries, services and reference implementations that enable engineering teams to develop production AI systems faster and more consistently.
- Make architectural trade-offs across model capability, reliability, latency, security, sovereignty, scalability and cost.
- Lead complex technical investigations and resolve systemic engineering and reliability issues across AI applications.
- Partner with AI Engineering, Central AI Platform, AI & Agent Operations, Data, Cybersecurity and business engineering teams to establish production engineering standards.
- Provide technical leadership through architecture and design reviews, code reviews, mentoring and hands-on engineering.
- Evaluate emerging AI infrastructure, agent frameworks and engineering approaches and determine where Singtel should build, adopt or standardise.
Skills for Success
- Bachelor's or Master's degree in Computer Science, Engineering, AI/ML or a related discipline, or equivalent practical experience.
- Typically 8+ years of software, platform, distributed systems, AI or ML engineering experience, with significant experience designing and operating production-grade systems.
- Deep software engineering expertise in Python, with strong foundations in APIs, distributed systems, concurrency, testing and system design.
- Hands-on experience architecting and building production LLM, RAG or agentic systems.
- Strong understanding of agent architectures, context engineering, retrieval, memory, tool/function calling and orchestration.
- Strong experience in evaluation, observability, testing or reliability engineering for complex production systems.
- Strong understanding of integration architectures including REST APIs, event-driven systems and modern agent/tool protocols such as MCP.
- Strong understanding of enterprise security including identity, authentication, authorisation, secrets management and least-privilege access.
- Experience designing reusable platforms, frameworks, SDKs or developer infrastructure adopted by multiple engineering teams.
- Strong cloud-native and distributed-systems engineering experience.
- Experience with agent or LLM frameworks such as LangGraph, LangChain or equivalent is advantageous, but deep engineering fundamentals are more important than familiarity with a particular framework.
- Ability to operate as a senior technical authority, influence engineering decisions across teams and translate rapidly evolving AI capabilities into robust production engineering practices.
Are you ready to say hello to BIG Possibilities?
Join Singtel to shape what's next and accelerate your career through meaningful work, continuous learning, and real impact.