AI Engineer

• Build and ship Android features using Kotlin.
• Create clean mobile flows for insurance, payments, claims, renewals and financial services.
• Work with product and design to simplify complex user journeys.
• Integrate backend APIs and ensure mobile flows are stable, secure and reliable.
• Improve app performance, crash rate, loading states, responsiveness and memory usage.
• Use analytics, user behaviour and production issues to improve the product.
• Build AI-assisted mobile experiences only where they genuinely improve the user journey.

Mobile Application Developer – AI Finance Agent

• Lead the technical relationship for post-sale customers and act as their trusted advisor on deployment, adoption, and value realization
• Own account health, adoption velocity, and ongoing technical deployment and success across your portfolio
• Conduct technical enablement and configuration sessions across our broad product portfolio
• Identify and validate use cases by embedding with customer teams to understand workflows and pain points
• Lead account level coordination across multiple workstreams, including new product activation, change management, and customer rollout and deployment planning
• Build strong relationships with executive sponsors and technical stakeholders and help align business goals with OpenAI capabilities
• Translate customer objectives into an actionable adoption roadmap with clear sequencing, milestones, and KPIs
• Partner with Solutions Architecture, Product, Engineering and Research by surfacing customer feedback, field patterns, and technical blockers and act as a cross functional navigator who keeps teams aligned, informed, and moving toward customer outcomes
• Guide value realization and measure impact through baselines, KPI definition, and post deployment reporting
• Facilitate workshops on use case design, adoption best practices, champion building, and internal enablement
• Help drive expansions by identifying high leverage opportunities where OpenAI’s platform can power new workflows or lines of business
• Serve as the technical advisor for existing customer implementations by guiding and optimizing account setup, configuration, etc.

AI Success Engineer

• Build customer-facing and internal product features end to end.
• Develop web flows, backend APIs, admin tools, dashboards and operational systems.
• Support products across insurance, payments, savings, investing, travel and financial services.
• Work with product, design, mobile and operations teams to launch fast.
• Integrate APIs, handle data flows and improve production reliability.
• Use analytics, feedback and production issues to improve features after launch.
• Help build tools that reduce manual work and improve speed across the business.

Full Stack Software Engineer – AI Neobank App

• Build AI-powered workflows, assistants, agents and automation systems.
• Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools.
• Work with product and engineering teams to turn manual processes into scalable AI-native systems.
• Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems.
• Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable.
• Prototype quickly, test with users or operators, then productionize what works.
• Improve speed, quality and consistency across workflows using AI where it creates real business value.

Applied AI Engineer – AI Neobank App

Mobile Developer – AI Neobank App

• Contribute to the design and development of AI agents integrated into live production systems
• Help build and maintain benchmark datasets to evaluate agent performance, accuracy, and safety
• Design and refine prompts, tool integrations, and agent workflows
• Implement, test, and optimize services and tooling across the stack — backend, data, scripting, automation, and glue code
• Collaborate closely with senior engineers on system design, multi-agent orchestration, and deployment
• Participate in code reviews, debugging, and documentation to ensure best practices
• Work in a team environment that encourages mentorship, knowledge sharing, and hands-on learning

AI Agent Engineer

Machine Learning Engineer

• Design and build training pipelines, data workflows, and model integration systems
• Develop infrastructure that accelerates research iteration and reduces turnaround time
• Build systems for data collection, curation, and preprocessing at scale
• Create tools and automation that move experiments toward production readiness
• Optimize data pipelines for reliability, performance, and observability
• Collaborate with ML researchers to understand their needs and remove technical blockers
• Work on model serving infrastructure and integration with the production framework
• Write clean, well-tested code that maintains high engineering standards
• Participate in code reviews and help raise the engineering bar across the team
• Contribute to shared tools, infrastructure, and cross-role projects (20% Time)
• Work with the dual-leadership model (Engineering Manager and Tech Lead) to understand priorities and technical direction
• Document systems and decisions to support team knowledge sharing

Software Engineer, ML Engineering

Applied AI Engineer – Finance Super App

• Partner with business team to identify and prioritize high-impact AI use cases, including buy-vs-build recommendations.
• Design and deliver AI products end-to-end, from problem definition through prototype, pilot, and production handover.
• Build AI-powered solutions.
• Develop robust datasets along with retrieval and reasoning pipelines across different business functionalities.
• Integrate with vendor AI platforms and internal AI solutions, reusing existing capabilities where possible.
• Instrument solutions to track adoption, quality, business value, ROI, cost, and risk.
• Partner with technology team to ensure secure, compliant, auditable, and supportable solutions.
• Run rapid evaluation cycles and contribute reusable components, patterns, and tools for wider adoption.

Forward Deployed Engineer, AI Engineer

• The Senior AI Engineer (Specialist) plays a pivotal role in designing, developing, and deploying GenAI/LLM, NLP and agentic AI solutions.
• Collaborates with cross-functional teams to transform structured + unstructured healthcare data into LLM-enabled products.
• Responsible for end-to-end delivery for AI workstreams from scoping to deployment/ monitoring.
• Leads feature engineering strategy; mentors juniors and performs code reviews on top of being hands on.
• Build and maintain reusable ML accelerators for standardization.

Machine Learning Engineer jobs in Singapore

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