Job Overview

Visa is hiring a Senior Software Engineer in Bengaluru for a full-time hybrid opportunity within its Corporate Reliability Engineering organization. This position focuses on combining software engineering, QA automation, reliability engineering, endpoint engineering, and AI-driven automation to improve the quality and operational stability of enterprise workstation environments.

The role is intended for a hands-on engineer with 3 to 5 years of experience who can turn operational challenges into maintainable engineering solutions. You will build automation services, agentic workflows, APIs, test frameworks, validation tools, and integrations that help reduce repetitive support work and improve release confidence. The work covers Windows and macOS environments and includes functional, regression, integration, compatibility, performance, and release certification testing.

A major part of the opportunity is applying agentic AI responsibly. Solutions are expected to include appropriate quality controls, human approval points, traceability, reusable components, and operational accountability rather than relying on uncontrolled automation.

Key Responsibilities

• Design, develop, test, and maintain agentic workflows and automation solutions for reliability engineering and endpoint support.
• Convert recurring operational problems, support patterns, and manual tasks into scalable automation.
• Develop reusable code, scripts, APIs, connectors, workflow components, and automated test frameworks.
• Integrate automation with approved enterprise systems, telemetry sources, knowledge repositories, support platforms, and operational workflows.
• Build automated validation and quality gates for agentic workflows and software releases.
• Develop workstation release certification solutions for Windows and macOS across supported device models and configurations.
• Create functional, regression, integration, compatibility, system, and performance test suites.
• Automate device provisioning, software installation, configuration, test execution, evidence collection, cleanup, rollback, and reporting.
• Measure CPU, memory, disk I/O, network utilization, login performance, application startup, responsiveness, crashes, and stability to identify regressions.
• Analyze logs, service desk tickets, endpoint telemetry, application behavior, and incident trends to identify reliability risks.
• Produce release scorecards, test evidence, quality metrics, and evidence-based deployment recommendations.
• Work with QA, Client Engineering, Information Security, support, infrastructure, and other cross-functional teams.
• Maintain runbooks, implementation notes, workflow documentation, decision records, and support materials.
• Continuously assess new AI, automation, testing, and reliability technologies that can improve engineering outcomes.

Required Skills

Candidates should have strong software development and automation fundamentals. The role requires proficiency in at least one programming or scripting language such as Python, PowerShell, Bash, JavaScript, TypeScript, or Java. Experience building APIs, automation scripts, workflow solutions, or agent-based applications is relevant.

You should understand source control, testing, debugging, technical documentation, secure development, code reviews, logging, monitoring, and production-readiness practices. The ability to analyze operational data and convert recurring issues into engineered solutions is particularly important.

Knowledge of enterprise endpoint operations is required, including Windows or macOS support, software deployment, patching, compliance, telemetry, and troubleshooting. Candidates should be able to investigate issues involving operating systems, applications, device drivers, endpoint security, management agents, network dependencies, and identity-related components.

Preferred Skills

Experience with automated test frameworks such as Playwright, Selenium, Appium, Robot Framework, pytest, or Pester is preferred. Practical experience creating repeatable and deterministic tests, diagnosing flaky tests, and separating product defects from test or environment failures is valuable.

Candidates with GenAI, Large Language Model, Retrieval-Augmented Generation, chatbot, Copilot Studio, or agentic workflow experience are encouraged to apply. Familiarity with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or comparable agent orchestration frameworks is also preferred.

Experience with ServiceNow, Jira, GitHub, Azure DevOps, Power Platform, Copilot Studio, observability platforms, endpoint telemetry, or enterprise support data can strengthen your profile. Knowledge of Model Context Protocol, tool calling, function calling, multi-agent patterns, vector databases, embeddings, semantic search, and knowledge retrieval systems is also useful.

Education

A Bachelor’s degree in Information Technology, Computer Science, Engineering, or a related field is listed as a basic qualification. Equivalent practical experience is also accepted according to the supplied job information.

Experience

The position requires 3 to 5 years of experience in software development, automation engineering, AI or ML engineering, agentic systems development, reliability engineering, platform engineering, endpoint engineering, or related technical roles.

Required Technologies

• Python
• PowerShell
• Bash
• JavaScript
• TypeScript
• Java
• Windows
• macOS
• APIs
• Source Control
• CI/CD
• GenAI
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Agentic AI
• Playwright
• Selenium
• Appium
• Robot Framework
• pytest
• Pester
• LangChain
• LangGraph
• CrewAI
• AutoGen
• Semantic Kernel
• ServiceNow
• Jira
• GitHub
• Azure DevOps
• Power Platform
• Copilot Studio
• Model Context Protocol (MCP)
• Vector Databases
• Embeddings
• Semantic Search
• Microsoft Intune
• Windows Autopilot
• MECM/SCCM
• JAMF
• Grafana
• Azure Monitor
• Splunk
• Datadog
• Dynatrace
• New Relic
• Nexthink
• Microsoft Endpoint Analytics

Soft Skills

Strong analytical thinking and problem-solving ability are central to this position. You should be able to investigate ambiguous operational problems, identify patterns, and translate findings into practical automation.

Clear written and verbal communication is also important because the engineer will work with global, cross-functional teams and explain technical concepts to both technical and non-technical stakeholders. Ownership, adaptability, curiosity, collaboration, and a willingness to learn emerging technologies are valuable qualities for the role.

Benefits of Working in this Role

This position offers hands-on exposure to modern software engineering, AI and agentic automation, QA automation, reliability engineering, endpoint platforms, observability, and enterprise technology operations. It provides an opportunity to work on solutions designed to reduce manual effort, improve release quality, and strengthen employee technology experiences.

The role also supports continued development across emerging AI engineering practices, automated testing, reliability engineering, and enterprise automation. Working with multiple engineering and operations functions can broaden both technical and cross-functional experience.

Work Mode

This is a hybrid position. Visa requires employees in this role to work from the office at least 3 days per week. The specific office days are expected to be confirmed by the Hiring Manager.

Location

The position is based in Bengaluru, Karnataka, India.

Who Should Apply

This opportunity is suitable for software engineers, automation engineers, AI or ML engineers, reliability engineers, platform engineers, and endpoint-focused engineers with 3 to 5 years of relevant experience.

Candidates who enjoy building automation rather than relying on repetitive manual support work may be a strong fit. Experience with Windows and macOS endpoint environments, automated testing, enterprise integrations, APIs, scripting, CI/CD, GenAI, or agentic workflows can be particularly relevant.

Career Growth

The role can help engineers develop deeper expertise across software development, QA automation, reliability engineering, endpoint engineering, AI-assisted automation, observability, and enterprise systems. Exposure to agent orchestration, RAG, LLMs, automated validation, and reliability practices can support long-term growth in modern engineering roles.

The position also encourages continuous learning and experimentation with emerging AI and automation patterns, providing opportunities to expand beyond a single technical discipline.

Application Advice

Tailor your resume to clearly demonstrate 3 to 5 years of relevant engineering experience. Highlight automation projects, software development work, test frameworks, endpoint engineering, reliability improvements, or AI-enabled solutions that you have delivered.

Mention the programming and scripting languages you have actually used, along with relevant experience in APIs, CI/CD, source control, Windows, macOS, automated testing, telemetry, or enterprise support environments. If you have worked with GenAI, LLMs, RAG, agent frameworks, MCP, vector databases, or AI-assisted automation, describe the practical outcome of that work.

Also emphasize experience with quality gates, regression testing, release validation, observability, troubleshooting, documentation, and cross-functional collaboration. Use measurable outcomes where they are genuinely supported by your experience.