Sr. SW AI Engineer

Visa Technology and Operations LLC is hiring a Sr. SW AI Engineer to build production-grade, agentic LLM systems for an AI-first engineering team.

Responsibilities

• Collaborate with stakeholders to interpret requirements for project components and incorporate feedback into designs and solution fixes
• Translate business requirements by verifying assumptions and escalating potential design issues to appropriate stakeholders
• Participate in system design and architecture, refining code plans and contributing to design documentation
• Contribute to project estimation and escalate issues that may cause delays
• Develop, implement, and maintain code for products, services, and components using established patterns, guidelines, and best practices
• Use debugging tools to validate assumptions and proactively flag issues
• Participate in code reviews to ensure coding standards are followed and address routine pull requests
• Create test plans and configure testing procedures to identify and resolve defects across multiple features
• Respond to support requests during on-call rotations, troubleshoot issues, and deploy fixes under guidance
• Leverage software developer tools to create, debug, and maintain code for components
• Stay current by using training resources to improve availability, reliability, efficiency, observability, and performance
• Design, implement, and tune multi-agent LLM workflows using agent orchestration frameworks such as LangGraph, LangGraph4j, and LangChain4j (declarative graph compilation, conditional routing, state persistence, dynamic runtime spawning)
• Build and maintain ReAct (Reasoning + Acting) agent loops where an LLM selects tools, interprets tool results, and continues until a terminal answer is reached
• Implement Supervisor/Orchestrator agent patterns to plan, spawn, and coordinate Specialist Sub-Agents using conditional graph edges and tool frameworks
• Develop MCP (Model Context Protocol) tool servers that expose enterprise data sources as callable tools for AI agents
• Implement and refine RAG pipelines including document ingestion and chunking (PDF/Word), embedding generation, vector storage (PostgreSQL + pgvector), and semantic similarity retrieval
• Integrate with enterprise LLM inference gateways via REST APIs (request shaping, prompt template management, token budget control, graceful degradation under unavailability)
• Design and implement agent memory architectures (short-term per-agent isolated context stores and long-term shared knowledge repositories)
• Implement confidence scoring and uncertainty quantification with threshold-based routing of low-confidence results to human review
• Build agent feedback loops by capturing human reviewer decisions and feeding structured corrections back into prompt templates and knowledge repositories
• Write LangChain4j/LangChain tool definitions (Java @Tool-annotated methods) and wire them into ReAct agents for data transformation, external API calls, and domain processing
• Build agentic audit trails with structured logs for tool calls, agent decisions, LLM prompt/response, and state transitions for traceability and explainability
• Develop and test Spring Boot microservices (Java 21, Spring Boot 3.5.x) that host AI orchestration engines, expose REST APIs, and integrate with upstream data source systems
• Author and maintain Helm charts and Jenkins CI/CD pipelines for containerized deployment of AI services to Kubernetes/OpenShift across multi-region on-premise data centers
• Develop and run end-to-end and integration tests for non-deterministic AI components, including prompt regression suites, tool call mock frameworks, output schema validators, and determinism gates for silent prompt drift

Requirements

• 2+ years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g., Masters, MBA, JD, MD, PhD)
• 3+ years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g., Masters, MBA, JD, MD)
• 2+ years of relevant work experience and a Bachelor’s degree, OR 5+ years of relevant work experience
• Experience in technologies/software systems or a directly related field (minimum two years)
• Experience developing and/or implementing web-based or mobile applications (minimum two years)
• Experience in system design and architecture for product components
• Experience in debugging and troubleshooting software issues
• Experience in code review and applying coding standards
• Experience in test planning and execution for software features
• Experience in responding to support requests and deploying fixes
• Experience in using software developer tools for code creation and maintenance
• Experience developing backend services in Java (Java 17+ preferred; Java 21 a strong plus)
• Familiarity with REST API design, Spring Boot, and JPA/ORM-based data access patterns
• Foundational understanding of LLM APIs including prompt construction, token limits, and response parsing
• Experience building and testing enterprise-scale web services (minimum one year)
• Experience working on client-facing project or technical teams (minimum one year)
• Experience integrating feedback into design and solution fixes
• Experience mentoring junior engineers and collaborating with cross-functional teams
• Hands-on experience building agentic AI systems using LangGraph, LangChain, LangGraph4j, or LangChain4j, including multi-agent graph construction, node/edge definitions, conditional routing, and state schema design
• Experience implementing the React prompting pattern (Thought Action- Observation) in a production or near-production LLM application
• Working knowledge of Model Context Protocol (MCP): server registration, tool schema definition (tools/list, tools/call), and client-side integration
• Experience building RAG pipelines: document chunking strategies, embedding models, vector database querying (pgvector, Pinecone, Weaviate, or equivalent), and retrieval relevance tuning
• Experience with prompt engineering including structured output enforcement (JSON schema), chain-of-thought prompting, few-shot example design, and system prompt management
• Experience building and monitoring LLM observability (token usage, latency per agent step, tool call success rates, output quality metrics)
• Experience with PostgreSQL including the pgvector extension for embedding storage and similarity search
• Experience deploying containerized workloads on Kubernetes or OpenShift, including Helm chart authoring, rolling deployments, and health probes
• Experience designing audit logging for AI agent decisions capturing inputs, reasoning traces, tool calls, and outputs in structured, queryable format
• Familiarity with Aspect-Oriented Programming (AOP) for cross-cutting concerns in Spring Boot (agent call logging, latency measurement, security enforcement)
• Experience with CI/CD pipelines (Jenkins or equivalent) for AI/ML service deployments including version gating and environment promotion strategies

Technologies

• Generative AI tools (e.g., ChatGPT, Microsoft Copilot)
• Large language models (LLMs)
• LangGraph, LangGraph4j, LangChain4j, LangChain
• ReAct (Reasoning + Acting)
• Model Context Protocol (MCP)
• REST APIs
• RAG (Retrieval-Augmented Generation)
• PostgreSQL, pgvector
• JPA/ORM
• Spring Boot, Java, Java 21, Spring Boot 3.5.x
• Helm charts, Jenkins CI/CD pipelines
• Kubernetes, OpenShift
• PDF, Word
• Pinecone, Weaviate
• JSON schema
• Aspect-Oriented Programming (AOP)

Compensation

• Estimated salary range: USD 110,700 - 171,800 per year
• May include potential sales incentive payments (if applicable)
• May be eligible for bonus and equity

Work Location and Schedule

• Location: Austin, TX (onsite)
• Work hours: Varies upon the needs of the department

Travel and Work Setting

• Travel requirement: 5-10% of the time
• Work setting: office setting
• Physical/mental requirements: sit and stand at a desk; communicate in person and by telephone; frequently operate standard office equipment such as telephones and computers

Benefits

• Medical
• Dental
• Vision
• 401(k)
• FSA/HSA
• Life Insurance
• Paid Time Off
• Wellness Program

Education: Bachelor’s Degree or an Advanced Degree

Minimum Experience: 2 years