Staff Software Engineer
Automation Anywhere
- Location
- Bengaluru, India
- Work model
- On-Site
- Level
- Staff
- Posted
- Aug 26, 2026
Skills
About this role
About Us
Automation Anywhere is the leader in Agentic Process Automation (APA), transforming how work gets done with AI-powered automation. Its APA system, built on the industry’s first Process Reasoning Engine (PRE) and specialized AI agents, combines process discovery, RPA, end-to-end orchestration, document processing, and analytics—all delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work, Automation Anywhere helps organizations worldwide boost productivity, accelerate growth, and unleash human potential. Staff Software Engineer Department: Engineering | Location: Bangalore, India | Level: E4 / Staff The Role We are looking for a Staff Software Engineer — an engineering leader who combines deep technical expertise with the ability to drive meaningful outcomes across team boundaries. You operate as a force multiplier: you elevate the engineers around you, close the gap between product vision and technical reality, and deliver systems that are built to last. You'll be equally comfortable writing production code and leading architectural discussions. You'll move fast, adapt quickly, and thrive in an environment where problems are complex, timelines are real, and impact is immediate.
What You'll Do
Lead end-to-end technical ownership of major features and platform components — from architecture and design through implementation, testing, deployment, and operation. Architect scalable, maintainable, cloud-native services that can evolve as product requirements change and user load grows. Integrate AI tools throughout your development workflow — using AI-assisted development tools for coding, testing, code review, and documentation — and help evangelize effective AI usage across your team. Collaborate closely with product managers, designers, data scientists, and peer engineers to translate business requirements into robust technical solutions. Write design documents and participate in architectural reviews; give and receive critical technical feedback. Identify and address technical debt, performance bottlenecks, and reliability gaps proactively. Mentor mid-level engineers through code reviews, design walkthroughs, and pairing sessions. Contribute to engineering culture: drive improvements to team processes, development standards, and on-call practices.
What You'll Bring
Experience & Depth 10+ years of software engineering experience, with at least 2 years in a staff-level role or functioning at that scope. Deep expertise in at least one technical area: backend systems, platform engineering, cloud infrastructure, data engineering, or AI/ML integration. A proven history of designing and shipping complex software systems end-to-end — not just features, but systems that other teams depend on. Strong debugging and troubleshooting skills; you can root-cause a hard production problem under pressure. Technical Breadth Solid across the full modern software stack: microservices, APIs, relational and non-relational databases, event streaming, cloud platforms, and container orchestration. Proficient in at least one backend language (Java, Go, Python, Node.js, or similar); experience with polyglot environments is a plus. Hands-on with Kubernetes, Helm, Terraform, and modern CI/CD (GitHub Actions, ArgoCD, or equivalent). Working knowledge of observability practices — distributed tracing, structured logging, SLO/SLA-based alerting (Datadog, OpenTelemetry, Prometheus). Exposure to AI/ML ecosystems: REST APIs for LLMs, prompt engineering, vector search, or embedding pipelines. AI-Native Development Actively uses AI-powered developer tools (Copilot, Claude Code, or similar) as part of daily development — not occasionally, but habitually. Can articulate when AI-generated code should be trusted, reviewed carefully, or discarded entirely. Interest in building AI-native product features: integrating LLM APIs, building agent-backed workflows, or wiring AI into