Senior Software Developer (Detection)

NorthStar HR Consultants; Pune District; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

NorthStar HR Consultants in Pune, Maharashtra, is seeking a Senior Software Developer (Detection) to own complex detection features end-to-end and build high-throughput, low-latency services at scale. You will collaborate across SRE, product and engineering teams, and mentor engineers while shaping architecture and testing strategies.

The role requires 5+ years backend experience in Go, Python, Node.js, or Java, with AI tooling fluency and cloud services knowledge.

Qualifications

• 5+ years building production backend services in Go, Python, Node.js or Java.
• Hands-on use of AI coding tools as part of workflow.
• Strong experience with cloud-hosted microservices and distributed systems.
• Relational and NoSQL database experience.
• Web/HTTP fundamentals and CDN concepts.
• Experience designing automated testing strategies and agile work.
• Ability to turn ambiguous problems into reliable systems.

Responsibilities

• Own complex detection features end to end from requirements through production rollout.
• Build high-throughput, low-latency services at global scale.
• Collaborate with SRE, product and other teams, owning services from spec to on-call.
• Design automated testing strategies to catch regressions.
• Contribute to architecture decisions and AI-enabled detection capabilities.
• Mentor engineers and participate in technical interviews.

Skills

Go

Python

Node.js

Java

AI tooling

Relational databases

NoSQL

Cloud microservices

HTTP fundamentals

Automated testing

Agile teams

Education

Master's degree

Tools

Docker

Kubernetes

GitHub Copilot

Claude Code

Cursor

Job description

Job Title - Senior Software Developer (Detection)

Job Location - Pune, Maharashtra

MUST Have Skills - 5+ years of exp in Golang, Python, Claude Code, Relational Database,

This team builds and runs the real-time services that process hundreds of millions of sessions a day, combining hundreds of signals, device and behavioral data, IP reputation, and increasingly agentic AI classification, to make risk decisions and enrich data in milliseconds. Its high-throughput, low-latency systems work, with real adversaries on the other side actively trying to break what you build.

What You'll be Doing

• Own complex detection features end to end, from ambiguous requirements through architecture, implementation, and production rollout
• Build and extend high-throughput, low-latency services that process device, behavioral, and risk signals at global scale
• Work cross-functionally with SRE, product, and other engineering teams that depend on detection signals, owning your services from spec through on-call
• Design automated testing strategies that catch regressions before adversaries do
• Weigh in on architecture and technical direction for the systems your team owns, including how new detection capabilities like agentic AI classification get built
• Mentor P1/P2 engineers and help raise the technical bar across the team
• Contribute to hiring through technical interviews and candidate evaluation

Must Have

• 5+ years building production backend services in Go, Python, Node.js, or Java (4+ years with a Master's degree)
• Hands-on daily use of AI coding tools such as Claude Code, GitHub Copilot, or Cursor as part of how you build software. This is a working requirement, not a nice to have. You should already have a workflow for using AI tools to write, test, review, and debug code faster, and be ready to help the team build better ones
• Strong experience with cloud-hosted microservices and distributed systems at scale
• Solid database experience across relational and NoSQL systems
• Working knowledge of web and HTTP fundamentals, including DNS, TLS, caching, and CDNs
• Experience designing and driving automated testing strategies
• Comfort taking ambiguous problems and turning them into shipped, reliable systems
• Experience working in agile teams (Scrum or Kanban)

Nice to Have

• Machine learning background, such as model integration, feature engineering, or applied ML in a fraud, risk, or trust context
• Frontend experience (React or similar) for full-stack detection tooling
• Experience with containers and orchestration (Docker, Kubernetes)
• Exposure to CI/CD pipeline design, ideally with AI-assisted test generation or code review