SW Engineer

Visa•Foster City, CA

2d•Hybrid

About The Position

Visa is seeking an experienced AI/ML Engineer to design, build, and scale next-generation artificial intelligence capabilities for Finance Technology, with a focus on the Source-to-Collections ecosystem. This role is centered on developing LLM-based applications, intelligent agents, AI-powered automation, scalable machine learning pipelines, and generative AI solutions that improve productivity, decision-making, process intelligence, and operational efficiency across Sourcing and Collections. This role is expected to be approximately 70% AI/ML-focused engineering and 30% core application development, automation, and platform integration.

Requirements

Hands-on experience designing, building, testing, and deploying AI capabilities that solve real enterprise problems.
Understand how to move from experimentation to production while balancing performance, reliability, security, and business value.
Comfortable working with LLMs, prompt engineering, embeddings, RAG architectures, intelligent agents, vector databases, model APIs, and orchestration frameworks.
Understand how to evaluate LLM outputs, reduce hallucinations, and build reliable AI experiences.
Experience developing scalable backend services, APIs, data pipelines, web applications, and cloud-native solutions.
Experience working with structured and unstructured data, extracting insights, automating workflows, and designing AI solutions.
Innovation and curiosity to apply AI, automation, and intelligent systems.
Ability to work effectively with product owners, engineers, architects, finance stakeholders, and leadership.
Ability to explain technical AI concepts clearly and translate business problems into AI-enabled solutions.
Continuous learning and staying current with emerging AI/ML technologies.
Bachelor’s degree with 6 months - 2 years of relevant AI/ML, data science, or software engineering experience.
Hands-on development experience with Python and Java.
Experience building backend services using Java, Spring, REST APIs, and enterprise application frameworks.
Strong foundation in AI/ML concepts, data engineering, NLP, LLMs, and modern software development practices.
Experience delivering production-grade LLM-based applications, AI agents, RAG solutions, or AI-powered automation platforms.
Experience with AI/ML frameworks and tools such as TensorFlow, PyTorch, scikit-learn, Hugging Face, MLflow, Docker, Kubernetes, or similar technologies.
Experience with large-scale data processing, distributed systems, cloud-native architectures, and enterprise data platforms.
Demonstrated ability to build scalable AI pipelines and integrate models into real-time or near-real-time enterprise systems.
Proven track record delivering AI/ML or generative AI projects with high quality and timely execution.
Experience with model evaluation, AI safety testing, hallucination mitigation, prompt/version management, guardrails, monitoring, and continuous improvement.
Experience ensuring AI solution quality through rigorous testing, validation, data quality checks, scalable ingestion frameworks, and observability.
Experience optimizing AI/ML application performance, including latency, cost, throughput, accuracy, reliability, and scalability.
Ability to measure and demonstrate productivity, operational, or business improvements through clear metrics and reporting.
Strong communication skills with the ability to explain complex AI concepts to technical and non-technical audiences.
Experience working with finance, procurement, sourcing, billing, collections, accounting, or enterprise business applications.
Experience collaborating across global, diverse, inclusive, and cross-functional teams.

Nice To Haves

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, Artificial Intelligence, Machine Learning, or a related field.
2 years of experience in a software engineering, AI engineering, machine learning engineering, or data engineering role.
Advanced degree or certifications in AI/ML, data science, cloud AI platforms, or generative AI preferred.

Responsibilities

Design, build, and scale next-generation artificial intelligence capabilities for Finance Technology.
Develop LLM-based applications, intelligent agents, AI-powered automation, scalable machine learning pipelines, and generative AI solutions.
Improve productivity, decision-making, process intelligence, and operational efficiency across Sourcing and Collections.
Integrate AI capabilities into existing enterprise systems.
Work with structured and unstructured data, extract insights, and automate workflows.
Design AI solutions that improve operational decision-making across finance processes.
Challenge existing processes and look for opportunities to apply AI, automation, and intelligent systems.
Collaborate with product owners, engineers, architects, finance stakeholders, and leadership.
Explain technical AI concepts clearly and translate business problems into AI-enabled solutions.
Stay current with emerging AI/ML technologies.
Manage multiple concurrent assignments across AI engineering, automation, and application development.