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Thoughtworks

Lead AI Engineer

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

Level's read on this job

  • Level rates this AI engineer role Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include RAG, fine tuning and NLP.
  • Level classifies it as a lead role.
  • Level lists 44 other open roles at Thoughtworks.

AI in this role

ragfine-tuningnlpai-safety

We are looking for a passionate and skilled AI engineer to lead the AI engineering practice at a team or program level. In this role, you will guide the design and delivery of generative AI solutions, shape the technical roadmap for your team(s), and ensure high standards of engineering excellence. You will provide technical leadership to a small group of engineers, collaborate with product and business partners, and act as a trusted technical consultant for stakeholders.

Due to the nature of the projects and specific client security clearance, this role requires the successful candidate to be a Singapore Citizen.

Job responsibilities

  • Lead a cross-functional team of software engineers, data scientists and other specialists delivering GenAI solutions.
  • Guide the design and delivery of AI-powered systems that are scalable, reliable and production-ready.
  • Set direction for technical decisions, ensuring AI solutions are optimized for performance, cost and maintainability.
  • Collaborate closely with product managers, designers and stakeholders to align technical solutions with business goals.
  • Establish and promote best practices in AI engineering, covering testing, guardrails, responsible AI, monitoring and documentation, while uplifting the team by sharing knowledge, tools and practices that enable both SMEs and generalists to contribute effectively.
  • Provide architectural guidance, balancing experimentation with delivery in short, safe cycles.
  • Review designs and code across the team, ensuring quality and consistency in AI-enabled features.
  • Set direction for GenAI application optimization to improve accuracy, performance, cost and know when model tuning is required.

Job qualifications

Technical Skills

  • Strong expertise in Python and modern software engineering practices, including CI/CD, testing, version control and system reliability.
  • Proven ability to design and integrate end-to-end AI systems, ensuring scalability, maintainability and performance.
  • Deep experience with GenAI and agentic frameworks, guiding teams in their effective use.
  • Expertise in building and scaling RAG pipelines and integrating vector databases into production systems.
  • Experience deploying AI solutions on major cloud platforms, using containers and CI/CD pipelines for reproducibility.
  • Skilled in LLMOps practices and monitoring production systems with observability tools.
  • Experience with fine-tuning, model adaptation and advanced use of ML/NLP frameworks.

Professional Skills

  • Ability to articulate complex technical concepts to non-technical audiences and influence senior decision-makers.
  • Proven ability to inspire, mentor and develop high-performing engineering teams, fostering a collaborative and inclusive environment.
  • Demonstrates the ability to anticipate technological trends and proactively shape the technical direction of the team.
  • Skilled in navigating complex internal and external dynamics, driving consensus and achieving technical and business goals.

Other things to know

Learning & Development

There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.

Responsible Use of AI in Recruitment

At Thoughtworks, we use AI tools to support our recruitment team with administrative tasks such as drafting communications, scheduling interviews and writing job descriptions.

Crucially, our AI tools do not screen, assess, rank or make hiring decisions. Every application is reviewed by our team and all selection decisions are made exclusively by our interviewers and hiring managers.

We are committed to fairness and responsible AI. We actively manage our AI systems by testing, monitoring for biased outcomes and implementing mitigation measures. We hold our third-party vendors to these same high standards through a rigorous governance process. For additional information, please see our full Thoughtworks AI Policy for Recruitment.

About Thoughtworks

Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary.

#LI-Hybrid

See here our AI policy.

How we rate this

Lead AI Engineer at Thoughtworks rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  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

RAGFine-tuningNLPAI Safety

Also common in AI engineer jobs at this level

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. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  3. What NLP problem have you worked on, and how did you measure whether it actually worked?
  4. How do you think about the risk of an AI system in this kind of role failing silently?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: RAG, Fine-tuning, NLP, and AI Safety. 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.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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