Senior Software Engineer - Go, AWS, Python

Responsibilities

• Design and deliver production backend services and APIs in Go, with opportunities to contribute to Python services and automation.
• Build event-driven and serverless systems on AWS using Lambda, API Gateway, SQS, Kinesis, IoT Core, S3, DynamoDB, IAM, and CloudWatch.
• Define secure, repeatable cloud infrastructure and deployments through Terraform.
• Build and improve telemetry, ingestion, analytics, and time-series data pipelines.
• Own features from technical design through release, monitoring, and post-production follow-through.
• Investigate customer escalations and incidents across application, infrastructure, data, and network layers; perform root-cause analysis and implement preventive improvements.
• Improve CI/CD, observability, runbooks, and shared on-call practices.
• Collaborate with platform, product, support, data, and ML teams on analytics, security, and AI-assisted diagnostic capabilities.
• Use approved AI-assisted engineering tools for code exploration, tests, documentation, and log analysis while validating correctness, security, performance, and maintainability.
• Raise engineering quality through code reviews, design feedback, and guidance to less-experienced engineers.

Requirements

• Experience building and supporting production backend or cloud services.
• Proficiency in Go, including service design, testing, debugging, and code review.
• Hands-on AWS experience and knowledge of event-driven or serverless patterns.
• Production experience with Terraform or comparable infrastructure-as-code tooling.
• Demonstrated ownership of delivery, troubleshooting, and operational follow-through.
• Strong Linux, networking, and distributed-systems fundamentals.
• Clear communication across teams and time zones.
• Typically 5–9 years of software engineering experience, including at least 3 years building production backend or cloud services with meaningful production-support or on-call ownership.

Nice-to-haves

• Production experience with Python.
• Experience with messaging, streaming, time-series databases, or telemetry pipelines.
• Experience with GitHub Actions, Grafana, tracing, Docker, ECS, or EKS.
• Practical use of AI-assisted engineering tools with sound validation and data-security judgment.
• Experience with multi-tenant SaaS, cloud data infrastructure, enterprise storage, file services, or security products.
• Experience turning ambiguous production incidents into durable engineering improvements.

Benefits

• Competitive compensation programs.
• Flexible time off and leave policies.
• Health and wellness coverage.
• Hybrid and flexible work arrangements.
• Employee referral and recognition programs.
• Professional development and learning support.
• Retirement and statutory benefits under Indian regulations.