1 month ago
Singapore, SingaporeSenior
Responsibilities
- Design, develop, maintain, and operate scalable data platforms, pipelines, APIs, integrations, backend services, and reusable engineering frameworks.
- Build secure, resilient, observable systems supporting real-time, streaming, and batch processing workloads.
- Build and integrate Generative AI applications, AI agents, and intelligent workflows using retrieval, tool calling, orchestration, memory, and human-in-the-loop patterns.
- Implement integrations with enterprise systems, APIs, data sources, and AI platforms using MCP and other interoperability standards.
- Design AI guardrails, governance controls, security mechanisms, and protections against prompt injection, unauthorized access, unsafe tool use, hallucinations, and policy violations.
- Implement AI monitoring, observability, telemetry, evaluation, and feedback frameworks while optimizing model selection, latency, throughput, token usage, and cost.
- Use AI-assisted development tools and coding agents throughout design, development, testing, debugging, code review, documentation, and software delivery.
- Collaborate with product, engineering, architecture, cybersecurity, data science, and business stakeholders and contribute to technical direction and engineering innovation.
Requirements
- At least 2 years of relevant work experience and a Bachelor's degree, or at least 5 years of relevant work experience.
- Strong programming skills in Java, Python, or similar languages.
- Experience building scalable data platforms, APIs, microservices, cloud-native applications, distributed systems, event-driven architectures, and streaming technologies such as Kafka.
- Experience with CI/CD, automated testing, observability, production support, data engineering, integration, governance, and platform architecture.
- Experience building or integrating Generative AI and LLM-powered applications, including RAG, vector search, embeddings, semantic retrieval, and context management.
- Understanding of agentic AI, tool calling, workflow orchestration, AI application design patterns, AI guardrails, governance, security controls, and responsible AI practices.
- Experience evaluating and optimizing AI solution quality, latency, token consumption, and cost.
- Experience with AI-assisted development platforms and coding agents such as GitHub Copilot, Copilot Agents, Claude Code, Cursor, Windsurf, or equivalent tools.
- Preferred experience with LangChain, LangGraph, Semantic Kernel, Spring AI, CrewAI, AutoGen, MCP, A2A communication, AgentOps, LLMOps, AI platform engineering, vector databases, knowledge graphs, enterprise search, context engineering, model evaluation, benchmarking, and AI observability.
- Preferred experience building AI and data solutions on Azure, AWS, or Google Cloud and in Digital Marketing, Customer Engagement, Personalization, or MarTech platforms.
- Strong analytical, problem-solving, and collaboration skills; mentoring engineers and influencing technical direction across teams are preferred.
Benefits
- The role requires at least 3 days in the office, with expectations confirmed by the Hiring Manager.
- Visa is an EEO Employer and provides consideration without regard to protected characteristics or qualified criminal history, consistent with applicable guidelines and law.
Tech Stack
Categories
AI ApplicationsData Engineering
About Visa
Visa builds and operates a global digital payments network that connects consumers, merchants, financial institutions, and governments. It earns fees for processing card transactions and offering risk, data, and value‑added services through VisaNet and products like tokenization and tap‑to‑pay. Founded in 1958 and headquartered in Foster City, California, Visa is a public company (NYSE: V) serving clients in more than 200 countries and territories.