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Singtel

Lead AI Engineer #AIDA

Singtel is hiring a Lead AI Engineer #AIDA in Singapore, Singapore. Level rates it ; you can apply on Singtel.

Level's read on this job

  • On Level's scale, this AI engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include LangChain, LangGraph and RAG.
  • Level classifies it as a lead role.
  • Level lists 473 other open roles at Singtel.
  • The role was posted in the last few days.

AI in this role

LangChainLangGraph
ragml-ops

Powering the Future with AIDA

To lead the next phase of our AI evolution, we’ve launched a new business unit AIDA – Artificial Intelligence & Data Analytics – a strategic engine driving our transformation designed to scale our AI ambitions with precision and purpose. This marks a pivotal shift in how we operate, innovate, and serve to embed intelligence into every layer of our business.

At Singtel, this is more than a technology upgrade. It’s a strategic transformation that redefines how value is created across the enterprise core—augmenting human capabilities and unlocking entirely new potential. It is a transformation journey by aligning people, platforms, and processes under one cohesive strategy. Our mission is to build AI literacy and foster a culture where intelligence empowers people.

We welcome you to join us on a transformational journey that’s reshaping the telecommunications industry — and redefining what’s possible with AI at its core. Grow with us in a workplace that champions innovation, embraces agility, and puts human potential at the heart of everything we do.

Be part of something BIG!

We are seeking an experienced Lead AI Engineer to oversee the design and delivery of AI and Agentic AI solutions across the organisation. You will act as the technical lead who works closely with solution architects to translate business and system requirements into clear development tasks, technical designs, and implementation plans.

You will guide a team of AI engineers and software engineers, provide hands on technical direction, review solution quality, and ensure that all AI components and software modules are secure, scalable, and ready for production. The role requires deep applied AI development experience, strong full stack engineering capability across frontend and backend, and the ability to drive engineering excellence through mentorship and leadership.

How you will make an impact:

  • Lead the end to end technical design of AI and Agentic AI solutions, ensuring alignment with enterprise architecture, security controls, and platform standards.
  • Translate high level requirements from architects and product owners into detailed technical specifications, development tasks, and implementation plans.
  • Oversee the full development lifecycle for AI, software, and automation workflows, providing hands on guidance and removing technical blockers for the team.
  • Provide technical leadership across backend, frontend, API integration, LLM orchestration, agent frameworks, and workflow automation to ensure consistency and quality.
  • Review and approve solution designs, architecture diagrams, data flows, and code contributions from senior and junior engineers.
  • Drive the integration of AI solutions with enterprise systems, ensuring robust connectivity through APIs, MCP and other frameworks, while enforcing best practices.
  • Guide the design of hybrid solutions that combine AI models, prompting logic, rule engines, middleware, RPA, and human in the loop elements in a coherent workflow.
  • Oversee the stability and performance of production systems, define monitoring strategies, and ensure issues are escalated and resolved quickly.
  • Establish engineering standards covering code quality, documentation, testing strategies, CI and CD practices, and security reviews.
  • Mentor and coach senior and junior AI engineers, provide structured guidance, and drive upskilling for full stack development, AI integration, and delivery discipline.
  • Work closely with platform teams, cybersecurity, data engineering, product owners, and business stakeholders to ensure alignment and timely delivery.
  • Own risk identification and mitigation across AI solutions, including fallback strategies, model behaviour oversight, and protection against misuse or unexpected outputs.
  • Represent the AI engineering team in architecture discussions, solution reviews, and governance forums.
  • Able to design and maintain RAG systems, including content ingestion, embedding, vector storage, retrieval tuning, and accuracy checks for enterprise use cases.
  • Drive continuous improvement for the marketplace recommender engine, enterprise AI services, and core reusable components.
  • Coordinate effort estimation, sprint planning, prioritisation, and resource allocation for the AI engineering team.
  • Ensure delivered solutions are secure, scalable, compliant, and ready for production deployment.
  • Keeping close watch on new developments in AI, running small proof of concept work to understand their value, and advising the team on which solutions are suitable for adoption.

Skills for Success:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence or a related technical field. Candidates with advanced specialisation in full stack engineering or AI engineering are preferred.
  • More than 7 years of hands on experience delivering full stack software and AI solutions, with at least 2 to 3 years in a senior or technical lead capacity supervising engineers. Proven experience designing end to end AI and Agentic AI solutions.
  • Strong full stack engineering capability across frontend, backend, API design and system integration, with deep proficiency in Python, TypeScript or NodeJS and SQL.
  • Experienced in designing and leading implementation of LLM based and agentic AI systems, including orchestration patterns using frameworks such as LangChain or LangGraph.
  • Strong capability in integrating AI solutions with enterprise platforms, covering RESTful APIs, gRPC, MCP and secure middleware components.
  • Solid understanding of authentication and authorization patterns including OAuth2, JWT and SSO technologies.
  • Hands on experience designing scalable cloud deployments on Azure, AWS or GCP with good understanding of CI and CD practices.
  • Proven ability to conduct technical reviews, enforce engineering standards, and guide other engineers in code quality, architecture and system performance.
  • Proven ability to troubleshoot complex issues across frontend, backend, APIs, AI models and middleware in production environments.
  • Experience in LLMOps/GenAIOps, MLOps, DevSecOps
  • Passion for applied R&D, staying ahead of AI advancements, and bringing innovative ideas into production.
  • Strong problem-solving ability, attention to detail, and ability to collaborate effectively across teams.
  • Capable to work in a cross-functional team (Software/AI engineers, data platform, business users).
  • Experience in building secure, enterprise-grade integrations.

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.

How we rate this

Lead AI Engineer #AIDA at Singtel rates 66 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGML OpsLangChainLangGraph

Pay

Typical AI engineer job
$184k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?
  3. What are the limits of LangChain that you've run into, and how did you work around them?
  4. What's a project where you used LangGraph hands-on?
  5. Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

  • List these exact terms on your resume: RAG, ML Ops, LangChain, and LangGraph. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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