Looking for a hands-on, high-impact Senior AI Engineer / Manager to spearhead our in-house Artificial Intelligence and Intelligent Automation initiatives within our Assurance practice.
Unlike traditional enterprise roles where you are a single cog in a massive team, this is an entrepreneurial, greenfield opportunity. You will sit at the center of a lean, high-visibility engineering team, working directly with department heads to architect our internal AI roadmap, build production-grade document intelligence pipelines, and mentor the next generation of engineers.
Candidates with strong technical execution ready to step up into their first formal leadership role are strongly encouraged to apply. Title banding (Assistant Manager / Lead vs. Full Manager) will be matched to current seniority with a structured pathway to management.
What You Will Do
... - Lead Core AI Initiatives: Architect, build, and deploy end-to-end AI applications tailored to audit, assurance, and corporate finance workflows—with an initial emphasis on complex document extraction, tabular parsing, and intelligent summarization.
- On-Premise & Cloud Infrastructure: Deploy hybrid systems across Microsoft Azure and our newly acquired on-premise GPU clusters. You will manage and optimize open-source/local models running strictly behind the firm’s firewall to preserve client data confidentiality.
- Team Mentorship & Growth: Provide direct technical guidance, code reviews, and mentorship to two junior AI engineers (2–3 years experience). As the engineering unit scales over the next 6 months, you will help identify skill gaps and recruit full-stack and machine learning talent.
- Production Engineering: Translate messy, real-world financial records (invoices, bank statements, contracts, ledgers) into structured data via OCR, NLP, and agentic workflows.
- Stakeholder Collaboration: Interface closely with the Head of Assurance to translate operational bottlenecks into robust technical roadmaps.
Who You Are
- 5+ Years of Proven Technical Experience: A grounded background in classical machine learning, with at least 2–3 years of hands-on experience deploying modern deep learning or LLM models into production environments.
- Solid Coding Chops: Exceptional programming skills (primarily Python) and strong software engineering fundamentals. Note: This is a ground-up engineering role, not a low-code/Copilot configuration position.
- Infrastructure Savvy: Familiarity with the Microsoft Azure cloud ecosystem and a strong willingness (or prior experience) to configure, host, and fine-tune models locally on bare-metal GPU machines.
- Leadership Ambition: You do not need prior team-management experience, but you must have the appetite, communication skills, and patience to coordinate delivery, mentor junior talent, and help establish engineering best practices.
- Practical Problem Solver: You care about business utility and latency over academic theory—focused on delivering reliable, reproducible tools that save thousands of operational hours.
What We Offer
- Direct Impact: Total ownership of greenfield AI products from day one, with direct visibility to executive leadership.
- Team Scale: Opportunity to help build and shape an engineering team projected to grow significantly within the year.
- Security & Stability: A competitive base salary, consistent performance-driven bonuses, and the backing of one of Singapore’s leading accounting and advisory networks.
To apply online please use the 'apply' function, alternatively you may contact Amir Hamzah at amir.hamzah @ randstad.com.sg.
(EA: 94C3609/ R1984348 )
