Senior Software Engineer - AI Initiative

Rippling; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Rippling is looking for a Senior Software Engineer to build foundational AI platform systems that support its strategy across HR, IT, and Finance. The role emphasizes hands-on coding with 60% of the time spent on implementation and debugging.

Candidates should have strong experience in backend programming, particularly in languages such as Python, Java, or Go. This position offers opportunities for growth within a fast-paced engineering environment.

Qualifications

• Experience building scalable backend systems in production (5–8 years).
• Strong programming skills in Python, Java, or Go required.
• Ability to work independently on design and execution.

Responsibilities

• Build foundational AI platform systems for HR, IT, and Finance.
• Contribute to AI platform capabilities like automated workflows.
• Own components from design to iteration and launch.

Skills

Backend programming

Coding in Python, Java, or Go

Distributed systems

System design

Collaboration skills

Education

5–8 years of software engineering experience

Experience in backend or platform engineering

Tools

Production systems

APIs

Databases

SQL

Job description

About Rippling

Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, such as payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.

About the AI Platform Team

The AI Platform team is one of Rippling's highest-priority engineering investments and sits at the center of the company's broader AI strategy. The team is building foundational infrastructure that powers AI capabilities across the entire product ecosystem, including HR, Payroll, Benefits, Recruiting, IT, Finance, Compliance, and Workforce Management. Rather than building standalone chatbots or simple LLM integrations, the team focuses on creating deeply integrated AI systems that understand Rippling's rich business context, permissions model, workflows, and enterprise data.

Core capabilities include AI agents, workflow automation engines, evaluation frameworks, feedback loops, data pipelines, and self-healing systems that can identify issues, surface insights, and automate complex enterprise workflows.

The platform operates with real business context, approvals, permissions, and auditability requirements, enabling customers to delegate operational tasks while maintaining control and governance.

What you will do

• Build foundational AI platform systems that support Rippling’s broader AI strategy across HR, IT, Finance, payroll, benefits, recruiting, compliance, and internal workflows.
• Work as a deeply hands‑on Senior Software Engineer, with about 60% of the time expected to be spent coding, debugging, reviewing code, and owning implementation.
• Contribute to the design and build‑out of AI platform capabilities such as background agents, automated workflows, evaluation systems, data pipelines, and model quality feedback loops.
• Help build systems that allow AI agents to automate repetitive enterprise workflows with the right permissions, controls, approvals, and auditability.
• Work on platform systems that support self‑healing and self‑improving workflows, where AI can detect negative product signals and help identify root causes.
• Partner with Staff Engineers, Product, Infra, Platform, and Engineering stakeholders to convert ambiguous product/platform problems into scalable technical solutions.
• Own well‑defined to moderately ambiguous components end‑to‑end — from design and implementation to testing, launch, monitoring, and iteration.
• Participate actively in design discussions, code reviews, debugging, production support, and operational improvements.
• Build reliable, scalable, and maintainable backend/platform systems that can support Rippling’s product ecosystem.

What’s exciting about this role

• This is not a generic chatbot or lightweight LLM wrapper role. The team is building core AI platform infrastructure that can make Rippling’s product surface more autonomous, context‑aware, and self‑improving.
• Engineers get exposure to AI agents, automated enterprise workflows, self‑healing systems, and custom intelligence layers built around Rippling-specific product context.
• The role offers strong learning, ownership, and growth opportunities for engineers who want to work at the intersection of backend/platform engineering and AI infrastructure.
• High‑potential Senior Engineers can grow toward Staff‑level scope over time.
• AI Platform team is lean and supports a broad set of internal stakeholders, creating a need for engineers who can ramp quickly and contribute with high ownership.
• Systems involve complex areas such as workflows, permissions, approvals, data quality, reliability, evaluations, and automation.
• Engineering must be comfortable with ambiguity, changing priorities, and rapid iteration.
• Coding is a core expectation; this cannot be filled by someone who is not actively hands‑on.

What you need to have

• 5–8 years of overall software engineering experience, preferably in backend, platform, infrastructure, distributed systems, or product engineering.
• Strong hands‑on coding ability; 60% coding is non‑negotiable. Must be comfortable writing production‑quality code, reviewing code, debugging issues, and owning implementation details.
• Strong programming knowledge in one or more backend/general‑purpose languages such as Python, Java, Go/Golang, C++, Scala, Kotlin, or C#.
• Experience building and operating scalable backend/platform systems in production.
• Good understanding of system design, API design, databases, data modeling, concurrency, observability, and production troubleshooting; ability to independently own well‑defined to moderately ambiguous technical problems from design to execution, launch, and iteration.
• Comfortable working in a fast‑paced product engineering environment with changing priorities and high ownership.
• Strong collaboration skills with Product, Infra, Platform, and Engineering stakeholders; good product judgment and ability to understand how engineering decisions impact customers and business outcomes.
• Ability to contribute to design reviews, code reviews, technical discussions, and team quality.
• For AI Platform specifically, practical curiosity or exposure to AI agents, LLM infrastructure, agentic workflows, ML/data infrastructure, inference pipelines, evaluations, automation systems, or adjacent AI systems is a strong plus.

What would be nice to have

• Prior experience in a high‑growth or hyper‑growth startup or product‑led technology company.
• Recent hands‑on exposure to AI agents, LLM tooling, AI infrastructure, automation platforms, evaluation systems, or data/ML pipelines.
• Strong knowledge of Python for AI/ML infrastructure, automation, agents, scripting, evaluations, or data pipelines.
• Strong SQL knowledge for querying, data‑heavy systems, analytics, workflow systems, reporting, and enterprise intelligence use cases.
• Experience with Go, Java, C++, or Scala in backend, platform, infrastructure, or distributed systems environments.
• Exposure to TypeScript/JavaScript if the role involves full‑stack, internal tooling, dashboards, or product surface ownership.
• Experience with workflow orchestration, background automation, reliability platforms, internal tools, or developer productivity platforms.
• Exposure to permissions, approvals, auditability, compliance, or security‑sensitive workflows.
• Prior exposure to fintech, HR tech, payroll, benefits, compliance, IT, enterprise SaaS, or workflow‑heavy platforms.
• Clear evidence of learning quickly, taking ownership, and operating well in ambiguous environments.

Technical Skills

• 5–8 years of strong software engineering experience, preferably in backend, platform, infrastructure, distributed systems, or product engineering.
• Hands‑on coding of 60% of the time; actively writing, reviewing, debugging, and owning production code.
• Strong coding ability in at least one backend/general‑purpose language.
• Preferred languages: Python, Java, Go/Golang, C++, Scala, Kotlin, or C#.
• Experience with production systems involving APIs, databases, reliability, observability, debugging, and scale.
• Ownership mindset; able to independently own features/components end‑to‑end and drive execution without constant hand‑holding.
• Strong learning agility and AI/platform curiosity. For AI Platform, show practical curiosity or exposure to AI agents, LLM infrastructure, automation systems, ML/data infra, inference, evaluations, or adjacent AI systems.