{"id":985064,"url":"https://alion.io/job/visa-sr-sw-ai-engineer","title":"Sr. SW AI Engineer","company":{"id":83,"name":"Visa","domain":"visa.com","url":"https://alion.io/company/visa","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":85,"open_postings":127,"ghost_share":0,"stale_share":0.575,"repost_share":0.024,"time_to_fill_p50_days":33,"computed_at":"2026-11-04T06:34:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":110700,"max":171800,"currency":"USD","period":"year","gross":null,"usd_annual":171800},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"ChatGPT","optional":false},{"name":"CI/CD","optional":false},{"name":"Copilot","optional":false},{"name":"Function Calling","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenShift","optional":false},{"name":"pgvector","optional":false},{"name":"PostgreSQL","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Spring Boot","optional":false},{"name":"Chain-of-Thought","optional":true},{"name":"Helm","optional":true},{"name":"Jenkins","optional":true},{"name":"Pinecone","optional":true},{"name":"Structured Outputs","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-09-16T23:22:59Z","employer_posted_date":"2026-10-02","last_verified_at":"2026-11-04T19:53:03Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":48},"description":"About Us\nVisa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.\nAt Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.\nJoin Visa and do work that matters - to you, to your community, and to the world. Progress starts with you.\nJob Description\nSoftware Development Engineers are expert problem-solvers and builders who design, implement, and improve software applications and systems. In this role, engineers spend approximately 60-75% of their time coding, working hands-on with code, data, and modern tools (including AI-assisted development, cloud services, and automation frameworks) to deliver secure, scalable, and high-quality technology solutions that drive business outcomes in the fintech sector. They collaborate with cross-functional teams - product managers, designers, data scientists, QA, operations, and compliance - to translate business requirements into robust technical solutions, all while adhering to best practices, security standards, and regulatory requirements.\nAll roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.\nThis role sits within an AI-first engineering team building production-grade agentic systems powered by large language models (LLMs). Engineers design and implement multi-agent orchestration frameworks, retrieval-augmented generation (RAG) pipelines, tool-calling integrations, and LLM inference services - all at enterprise scale on on-premise infrastructure.\nKey Responsibilities:\nCollaborate with stakeholders to interpret requirements for project components and incorporate feedback into future designs or solution fixes.\nTranslate business requirements by verifying assumptions and escalating potential design issues to appropriate stakeholders.\nParticipate in system design and architecture, refining code plans and contributing to design documentation.\nContribute to project estimation and escalate issues that may cause delays.\nDevelop, implement, and maintain code for products, services, or components, applying coding patterns, guidelines, and best practices.\nApply debugging tools to verify assumptions and proactively flag issues before they occur.\nParticipate in code reviews to ensure coding standards are followed and address routine pull requests.\nCreate test plans and configure testing procedures to identify and resolve defects for multiple features.\nRespond to support requests during on-call rotations, troubleshooting issues and deploying fixes under guidance.\nLeverage and build knowledge of software developer tools to create, debug, and maintain code for components.\nRemain current in skills by investing time in training resources to improve product availability, reliability, efficiency, observability, and performance.\nAI & Agentic Systems\nDesign, implement, and tunemulti-agent LLM workflowsusing agent orchestration frameworks (e.g., LangGraph, LangGraph4j, LangChain4j), including declarative graph compilation, conditional routing between agent nodes, state persistence, and dynamic agent spawning at runtime.\nBuild and maintainReAct (Reasoning + Acting) agent loops- iterative Reason→Act→Observe cycles in which an LLM selects tools, interprets tool results, and continues until a terminal answer is produced.\nImplementSupervisor/Orchestrator agent patternswhere a Lead Agent dynamically plans, spawns, and coordinates Specialist Sub-Agents using conditional graph edges and tool frameworks.\nDevelopMCP (Model Context Protocol) tool serversthat expose enterprise data sources as callable tools for AI agents, enabling natural-language-driven access to structured backend systems.\nImplement and refineRAG (Retrieval-Augmented Generation) pipelines: document ingestion and chunking (PDF/Word), embedding generation, vector storage (e.g., PostgreSQL + pgvector), and semantic similarity retrieval to ground LLM responses in authoritative source documents.\nIntegrate withenterprise LLM inference gatewaysvia REST APIs, including request shaping, prompt template management, token budget control, and graceful degradation under service unavailability.\nDesign and implementagent memory architectures- both short-term per-agent isolated context stores and long-term shared knowledge repositories used across agent workflows.\nBuildconfidence scoring and uncertainty quantificationmechanisms for AI-generated outputs, including threshold-based routing of low-confidence results to human review.\nImplementagent feedback loops- capturing human reviewer decisions and feeding structured corrections back into prompt templates and knowledge repositories to continuously improve model behavior.\nWriteLangChain4j / LangChain tool definitions(e.g., Java@Tool-annotated methods) and wire them into ReAct agents for data transformation, external API calls, and domain-specific processing.\nBuild and maintainagentic audit trails- structured logs capturing every tool call, agent decision, LLM prompt/response, and state transition for traceability and explainability.\nDevelop and testSpring Boot microservices(Java 21, Spring Boot 3.5.x) that host AI orchestration engines, expose REST APIs for downstream consumers, and integrate with upstream data source systems.\nAuthor and maintainHelm chartsandJenkins CI/CD pipelinesfor containerized deployment of AI services to Kubernetes/OpenShift clusters across multi-region on-premise data centers.\nBuildend-to-end and integration testsfor non-deterministic AI components - including prompt regression suites, tool call mock frameworks, agent output schema validators, and determinism gates to catch silent prompt drift before production.\nVisarequiresat least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.\nQualifications\nBasic Qualifications:\n2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)\nPreferred Qualifications:\n3 or more 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)\n2+ years of relevant work experience and a Bachelor's degree, OR 5+ years of relevant work experience.\n3 or more 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).\nExperience in technologies/software systems or a directly related field (minimum two years).\nExperience in developing and/or implementing web-based or mobile applications (minimum two years).\nExperience in system design and architecture for product components.\nExperience in debugging and troubleshooting software issues.\nExperience in code review and applying coding standards.\nExperience in test planning and execution for software features.\nExperience in responding to support requests and deploying fixes.\nExperience in using software developer tools for code creation and maintenance.\nExperience developing backend services inJava(Java 17+ preferred; Java 21 a strong plus).\nFamiliarity withREST API design, Spring Boot, and JPA/ORM-based data access patterns.\nFoundational understanding ofLLM APIs- prompt construction, token limits, and response parsing.\nExperience building and testing enterprise-scale web services (minimum one year).\nExperience working on client-facing project or technical teams (minimum one year).\nExperience in integrating feedback into design and solution fixes.\nExperience in mentoring junior engineers and collaborating with cross-functional teams.\nHands-on experience buildingagentic AI systemsusingLangGraph,LangChain,LangGraph4j, orLangChain4j- specifically multi-agent graph construction, node/edge definitions, conditional routing, and state schema design.\nExperience implementing theReact prompting pattern(Thought → Action → Observation) in a production or near-production LLM application.\nWorking knowledge ofModel Context Protocol (MCP)- server registration, tool schema definition (tools/list,tools/call), and client-side integration.\nExperience buildingRAG pipelines: document chunking strategies, embedding models, vector database querying (pgvector, Pinecone, Weaviate, or equivalent), and retrieval relevance tuning.\nExperience withprompt engineering- including structured output enforcement (JSON schema), chain-of-thought prompting, few-shot example design, and system prompt management.\nExperience building and monitoringLLM observability- tracking token usage, latency per agent step, tool call success rates, and output quality metrics in production.\nExperience withPostgreSQLincluding the pgvector extension for embedding storage and similarity search.\nExperience deploying containerized workloads onKubernetesorOpenShift, including Helm chart authoring, rolling deployments, and health probes.\nExperience designingaudit loggingfor AI agent decisions - capturing inputs, reasoning traces, tool calls, and outputs in a structured, queryable format.\nFamiliarity withAspect-Oriented Programming (AOP)for cross-cutting concerns such as agent call logging, latency measurement, and security enforcement in Spring Boot.\nExperience withCI/CD pipelines(Jenkins or equivalent) for AI/ML service deployments, including version gating and environment promotion strategies.\n\nInformation for US Applicants\nFor roles located in the US, the estimated salary range for this position is $110,700.00 to $ 171,800.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.Work Hours\nVaries upon the needs of the department.\nTravel Requirements\nThis position requires travel 5-10% of the time.\nMental/Physical Requirements\nThis position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.\nVisa is an EEO Employer\nQualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. 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Docs: https://alion.io/developers"}}