Sr. SW Engineer - Agentic Developer (Java/Python, 3-5 yrs of experience)

Visa Corporate IT has embarked on a major transformation journey to become an engineering-first organization where reliability, automation, customer experience, and end-user productivity are central to how we operate.

As part of this transformation, Corporate Reliability Engineering is focused on shifting from reactive support to proactive, predictive, and preventative engineering practices that reduce operational toil, improve service reliability, and enable scalable support across Visa’s global workforce.

The Agentic Developer, Corporate Reliability Engineering will be responsible for designing, building, testing, and maintaining agentic automation solutions that improve reliability, reduce manual effort, and accelerate problem resolution across Corporate IT services.

This role will develop intelligent workflows, reusable automation components, integrations, and human-in-the-loop solutions that help CRE teams predict issues, automate response, prevent recurrence, and continuously improve service outcomes.

This role is an Individual Contributor I5 / Analyst-level position for a technically strong developer who can translate operational challenges into well-engineered solutions.

The successful candidate will apply software engineering practices, secure development standards, automation, telemetry, workflow orchestration, and GenAI/agentic capabilities to deliver measurable improvements in reliability and employee experience.

Visa’s Agentic Toolchain materials describe agentic work as more than using AI for individual tasks; it includes persistent sessions, shared context, built-in quality gates, human approval points, telemetry, reusable artifacts, and lifecycle integration from product intent through engineering execution, release, and outcomes. This role will apply those same principles to CRE use cases where automation, reliability, and operational accountability are critical.

The ideal candidate should be passionate about:

• Agentic Automation Design: Design, build, and maintain agentic workflows that support CRE operational outcomes, including incident reduction, automated triage, knowledge retrieval, service health analysis, and repeatable remediation patterns.
• Human-in-the-Loop Engineering: Create workflows that combine automation with clear human approval gates, decision points, auditability, and escalation paths where required.
• Reusable Agentic Components: Develop reusable prompts, scripts, workflow templates, APIs, connectors, and automation modules that can be applied across multiple CRE-supported services.
• Persistent Context and Knowledge Reuse: Build solutions that preserve operational context, decisions, outputs, and lessons learned so teams do not repeatedly start from scratch.

• Code Development: Create extensible, maintainable, and secure code for automation services, workflow components, scripts, and integrations.
• API and Systems Integration: Build integrations with approved enterprise platforms, support tools, telemetry sources, knowledge repositories, workflow systems, and GenAI/agentic platforms.
• Automation of Operational Toil: Identify repetitive manual tasks across CRE and convert them into reliable automation patterns that improve speed, consistency, and scalability.
• CI/CD and Release Practices: Contribute to automated validation, deployment readiness, and controlled release practices for agentic workflows and automation solutions.

• Predictive and Preventative Engineering: Develop solutions that help identify patterns, risks, and recurring issues before they become widespread incidents.
• Incident and Problem Management Enablement: Build tools and workflows that improve triage, root cause analysis, known error detection, remediation recommendations, and post-incident learning.
• Service Health and Telemetry: Use operational data, logs, metrics, ticket trends, and user-experience signals to inform automation opportunities and measure effectiveness.
• Continuous Improvement: Partner with CRE teams to identify reliability gaps, automation opportunities, and process improvements that reduce incidents, escalations, and manual support effort.

• Automated Validation: Build automated checks and tests that validate workflow behavior, integration accuracy, data quality, and expected outcomes before release.
• Quality Gates: Implement quality gates that prevent incomplete, unsafe, or low-confidence automation from progressing without review.
• Regression Testing: Create repeatable tests to ensure updates to prompts, workflows, scripts, integrations, and automation logic do not break existing capabilities.
• Release Readiness Metrics: Produce clear reporting that demonstrates test coverage, pass/fail results, risk areas, and readiness for production use.

• Automation Dashboards: Partner with analytics and operations teams to develop dashboards that show automation adoption, effectiveness, reliability impact, time saved, and recurring issue reduction.
• Outcome Measurement: Define success metrics for each agentic solution, including reliability improvement, reduced manual effort, improved response time, improved knowledge reuse, or reduced recurrence.
• Trend Analysis: Analyze recurring incidents, service degradation patterns, ticket drivers, and operational bottlenecks to identify high-value automation candidates.
• Executive-Ready Communication: Translate technical outcomes into concise business impact statements for CRE, CIT, and leadership stakeholders.

• Cross-Functional Collaboration: Work closely with CRE engineers, Client Engineering, Microsoft Backend, Workstation Vulnerability Remediation, QA, Service Desk, Onsite Support, Information Security, Architecture, and Product teams to deliver automation aligned to operational needs.
• Stakeholder Communication: Communicate technical concepts, solution design, risks, and results clearly to both technical and non-technical audiences.
• Documentation and Knowledge Sharing: Maintain documentation, runbooks, design notes, workflow logic, decision records, and support guides for all agentic solutions.
• Engineering Culture: Promote engineering-first practices within CRE by encouraging automation, reusable design, code quality, peer review, testing discipline, and continuous learning.

• Design, develop, test, and maintain agentic workflows and automation solutions for Corporate Reliability Engineering.
• Translate CRE operational pain points into technical requirements, workflow designs, implementation plans, and measurable outcomes.
• Build maintainable code, scripts, APIs, connectors, and reusable automation components.
• Integrate automation solutions with approved enterprise systems, telemetry sources, knowledge repositories, and operational workflows.
• Apply secure development practices, coding standards, code reviews, testing, and documentation.
• Develop automated tests, validation logic, quality gates, and release readiness reporting for agentic workflows.
• Analyze incident, ticket, telemetry, and service-health data to identify automation and reliability improvement opportunities.
• Partner with CRE and cross-functional teams to reduce manual toil, improve reliability, and prevent recurring issues.
• Document workflows, support models, runbooks, and operational handoff materials.
• Continuously evaluate new tools, technologies, and agentic patterns that can improve CRE effectiveness.

• Deliver reliable agentic workflows and automation solutions that reduce manual effort and improve CRE operational outcomes.
• Successfully design, develop, and deploy production-ready AI agents that automate business workflows while meeting security, compliance, and operational requirements.
• Increase automation coverage across recurring CRE support scenarios.
• Reduce repetitive ticket handling, manual triage, and repeated troubleshooting effort.
• Improve speed, consistency, and quality of incident/problem analysis.
• Build reusable automation components that can scale across multiple services and teams.
• Produce clear documentation, test evidence, quality metrics, and business impact reporting.
• Demonstrate responsible use of GenAI and agentic automation through human approval points, quality gates, auditability, and secure engineering practices.

Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.

• Bachelor’s degree in Information Technology, Computer Science, Engineering, or a related field, or equivalent practical experience.
• 5 years of experience in software development, automation engineering, AI/ML Engineering, agentic systems development, reliability engineering, platform engineering, endpoint engineering, or related technical roles.
• Demonstrated experience developing maintainable code, scripts, automations, integrations, or workflow-based solutions and agent-based applications.
• Proficiency in one or more programming or scripting languages such as Python, PowerShell, Bash, JavaScript/TypeScript, Java, or similar, with preference for experience building AI, LLM, API, and agent orchestration solutions.
• Experience with APIs, source control, testing, debugging, and technical documentation, nd core Agentic AI capability.
• Familiarity with Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), agent frameworks, or AI orchestration concepts.
• Understanding of secure development practices, code review, and production-readiness expectations.
• Strong analytical and problem-solving skills with the ability to convert operational issues into engineered solutions.
• Ability to work independently and collaboratively across global, cross-functional teams.
• Strong written and verbal communication skills with the ability to explain technical concepts to non-technical stakeholders.

• Experience building GenAI, LLM, RAG, chatbot, Copilot Studio, agentic workflow, or AI-assisted automation solutions.
• Hands-on experience with agent orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
• Familiarity with Visa Agentic Toolchain concepts, including persistent sessions, shared context, quality gates, reusable artifacts, human approval points, and telemetry-driven outcomes.
• Experience with ServiceNow, Jira, GitHub, Azure DevOps, Power Platform, Copilot Studio, observability platforms, endpoint telemetry, or enterprise support data.
• Experience with reliability engineering, incident management, problem management, root cause analysis, or operational automation.
• Experience building dashboards, reports, or metrics to demonstrate automation effectiveness and business impact.
• Familiarity with Model Context Protocol (MCP), tool-calling patterns, function calling, and multi-agent architectures.
• Experience with CI/CD pipelines, automated testing, release validation, or controlled deployment processes.
• Understanding of ITIL practices, enterprise change management, support workflows, and service reliability principles.
• Experience working with vector databases, embeddings, semantic search, and knowledge retrieval systems.
• Ability to identify repeatable support patterns and convert them into scalable automation.
• Curiosity and adaptability in learning emerging AI, automation, and reliability engineering practices.

Visa is an EEO Employer

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.

Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.