Top AI Jobs in Singapore

Design and implement scalable LLM-powered applications, microservices, and APIs. Build AI agents, RAG-enabled semantic search, vector DB integration, CI/CD pipelines, and guardrails. Collaborate with stakeholders, own backend and full-stack development, and support DevOps, testing, and production reliability.

The Director, AI Solutions Engineer leads AI integration in marketing, develops APIs and UIs, ensures compliance and security, and provides technical support for AI models.

Serve as a technical bridge between customers and engineering to define requirements, run discovery workshops, translate business needs into user stories, support cloud-native and AI solution design, assist pre-sales POCs, work in Agile teams on backlog prioritization, coordinate UAT and production rollouts, and provide technical-business advisory throughout delivery.

Build and ship AI-driven GTM systems: outbound lead engine, inbound/lifecycle automations, AI-assisted content pipeline, data/reporting layer, and fast production patches to eliminate manual marketing workflows.

Lead Enterprise AI initiatives by designing, developing, and deploying AI/GenAI solutions. Partner with data engineers, technologists and business stakeholders to prototype, integrate, validate and benchmark LLM and advanced-model applications, manage expectations, and translate analytic results into business outcomes.

Work with the CTO and leadership to design and implement AI productivity solutions; research and prototype emerging AI technologies; collaborate across teams and continents; translate AI theory into scalable business applications and communicate technical ideas to non-technical stakeholders.

Work with stakeholders to define analytics problems and build deployable solutions: automate reports, perform data exploration and preprocessing for structured and unstructured data, integrate data into the enterprise platform, and develop and deploy machine learning, deep learning and Generative AI / LLM models.

Drive the expansion of software development and AI services by managing client relationships, building sales pipelines, and negotiating contracts.

Lead and govern a program composed of multiple projects: plan, align scope with business priorities, manage risks and interdependencies, coordinate stakeholders, report status to senior management, drive cross-team collaboration, and optimize resourcing and budgeting.

Lead technical strategy with channel partners across ASEAN to build repeatable Microsoft Cloud and AI Workforce offerings (Copilot, Power Platform, Agents). Drive architecture design, workshops, POCs, offer development, partner enablement, and co-sell execution to convert technical capability into scalable revenue and customer outcomes.

Lead applied-AI innovation across the full lifecycle: discover problems, prototype and pilot AI/ML (including Generative and Agentic AI), then hand over to product and engineering. Mentor a small team, collaborate with stakeholders and senior leadership, and build healthcare-focused IP and production-ready AI capabilities.

Lead end-to-end reconciliation, automation and AI enablement initiatives across the bank. Configure and maintain SmartStream TLM and equivalent platforms, design future-state processes, develop automation and dashboards, conduct testing and production rollout, and ensure governance, risk controls, audit readiness and stakeholder management.

Lead design and implementation of Red Hat OpenShift AI platform solutions for enterprise customers across ASEAN. Deploy and manage AI/ML workloads, architect generative and agentic AI solutions, run discovery and design workshops, support pre-sales and proofs-of-concept, define platform best practices, mentor junior consultants, and contribute to internal playbooks and open-source AI initiatives.

Design and deliver end-to-end, production-ready AI solutions and architectures across enterprise use cases. Implement code and pipelines (primarily Python), integrate models and services, build proofs-of-concept for LLMs/generative AI, establish MLOps and governance, and mentor engineering teams while aligning with global AI architecture and security standards.

Design and build production-grade AI solutions (knowledge assistants, document intelligence, automation, decision support, predictive analytics). Develop end-to-end AI pipelines, write production-quality Python code, perform prompt engineering, RAG, model fine-tuning, and deploy on cloud platforms while ensuring security, governance, and responsible AI practices.

Support the CEO by turning priorities into execution across product, hiring, licensing, partnerships and market launches. Track OKRs, decisions, blockers, prepare briefs and updates, coordinate cross-functional teams, identify execution gaps, and own urgent cross-departmental problems.

Design, build, and deploy AI and ML solutions (predictive and generative) for customer-facing and operational banking use cases. Work with large structured and unstructured datasets, apply deep learning/NLP/reinforcement techniques, explore agentic AI and RAG, collaborate with cross-functional teams, and communicate insights through visualization and storytelling.

Operationalise the bank's Responsible AI principles by implementing AI governance frameworks and model management platforms, conducting AI risk/materiality assessments, advising business units, reviewing high-risk AI use cases, monitoring regulations, and preparing regulatory-grade governance reports.

As an AI Engineer, you'll build prototypes, design system architectures, write code, integrate AI services, and manage deployments, ensuring software solutions meet public sector needs.

The AI Engineer builds prototypes, designs system architectures, writes production-quality code, manages deployments, and collaborates on AI platform services for government applications.

The Research Associate will assist with legal research in AI law, data protection, and cybersecurity law, compiling summaries and developing data governance practices.

The Research Associate will work on human-like traffic simulations, focusing on traffic behavior modeling and experimental validation using large datasets.

Conduct innovative research in advanced machine learning focusing on recommendation systems and graph neural networks, designing novel models, and analyzing large-scale data.

AI Engineers will drive AI projects, mentor apprentices, develop solutions, support recruitment, and foster community through workshops. Requires expertise in AI/ML, Software Engineering, and good communication skills.

The Research Engineer will conduct research, develop algorithms, design experiments, translate concepts into prototypes, and analyze data, focusing on sustainable digital solutions.