Top AI & Machine Learning Jobs

Lead end-to-end architecture for agentic AI solutions, including multi-agent workflows, tool calling, memory, retrieval, human-in-the-loop controls, and cloud deployment. Define security, resilience, scalability, latency, cost, observability, and governance standards. Select models, cloud services, vector search technologies, and frameworks while evaluating build-versus-buy decisions. Establish AIDLC stages, architecture decision records, evaluation criteria, release gates, and AI safety controls for banking-critical systems.

Lead AI governance and risk initiatives for a major investment bank. Translate evolving AI regulations into practical policies, controls, and governance frameworks; monitor regulatory change; coordinate engagements across functions and jurisdictions; oversee AI use cases; and report risks, developments, deliverables, and governance metrics to senior management. Partner with Compliance, Legal, Risk, Technology, and business stakeholders to promote safe and responsible AI adoption.

Build and deploy production-ready AI agents and agentic solutions for clients. Translate business requirements into AI applications through prototyping, testing, demonstrations, iteration, and deployment. Collaborate with stakeholders and cross-functional teams while adapting solutions to client architectures and platforms such as Snowflake and Databricks.

Lead the design and delivery of production-grade enterprise decision management solutions for financial services clients across Asia. Responsibilities include decision architecture, predictive modeling, optimization, business rules engineering, model governance, LLM integration, and feedback-loop monitoring. Advise senior stakeholders on decision automation, mentor team members, support proposals and client workshops, and help build Capco’s decision intelligence practice. The role requires deep experience across insurance or wealth management decision logic, classical AI, BRMS platforms, scorecards, modern machine learning, and regulated financial services governance.

Build and deploy production-grade AI solutions for insurance and financial services, including multi-agent workflows, LLMs, RAG systems, neural networks, and automation pipelines. Responsibilities include model training and optimization, backend development, cloud deployment, production monitoring, regulatory compliance, ethical AI, troubleshooting, code reviews, and collaboration with technical and business stakeholders.

Designs and delivers enterprise-scale generative AI and agentic AI architectures, including foundation model integrations, orchestration, cloud-native infrastructure, MLOps pipelines, monitoring, and production deployment. The role guides architecture from concept through implementation, aligns technology with business objectives, collaborates across teams, mentors colleagues, and contributes to AI thought leadership.

Designs agentic AI architectures and technical roadmaps for financial services clients. Translates business and technical requirements into scalable AI platforms, memory architectures, multi-agent systems, tool workbenches, and implementation requirements. Advises C-suite stakeholders, oversees AgentOps tracing and monitoring, establishes AI governance and security guardrails, and creates reusable architectures and methodologies. Collaborates across business, IT, risk, compliance, and consulting teams.

Designs agentic AI architectures and roadmaps for financial-services clients. Translates business and technical requirements into scalable architectures, develops reusable reference patterns, and advises C-suite stakeholders. Oversees AI memory, multi-agent systems, tool workbenches, AgentOps, monitoring, tracing, evaluation, security, and governance. Collaborates with risk and compliance teams to implement guardrails and communicates technical concepts to technical and non-technical audiences.

Designs agentic AI architectures, roadmaps, implementation requirements, memory systems, multi-agent platforms, monitoring and evaluation frameworks. Advises financial-services executives, translates business and technical requirements, establishes AI governance and security guardrails, and creates reusable architecture patterns and methodologies. The role collaborates with business, IT, compliance, and risk teams while overseeing cloud-based AI solution delivery.

Develop data science and AI solutions using Python and Django, including data collection, labeling, curation, feature engineering, classical machine learning, and generative AI. Deploy models to production using CI/CD, Airflow, and MLflow; automate modeling pipelines and monitor model drift. Collaborate with stakeholders in Agile Scrum teams, improve testing and automation practices, and analyze business requirements.