Senior Backend-Focused Full-Stack Engineer at Nirmata contributing to an AI-powered Kubernetes governance platform by owning backend systems and ensuring production readiness.
Responsibilities
Define, own, and evolve the architecture of core data-heavy subsystems, balancing scalability, reliability, and cost, with a 2–5 year technical horizon aligned to business goals.
Take end-to-end ownership of critical areas of the Nirmata Policy Management cloud platform, from technical design and implementation through deployment and operational maturity.
Lead the design and delivery of AI/ML-powered features, translating ambiguous product ideas into production-ready systems with clear performance, reliability, and cost constraints.
Partner closely with Product, Platform, and Customer-facing teams to ensure features are well-integrated, observable, and optimized for long-term maintainability—not just short-term delivery.
Set a high engineering bar through hands-on code reviews, architectural guidance, and direct accountability for code quality, security, and operational readiness.
Proactively identify technical gaps and opportunities, introduce new technologies or patterns where they add real value, and lead technical learning across the team by example.
Requirements
Bachelor's or Master's degree in Computer Science or a related field.
3 to 10 years of professional experience in software development.
Strong proficiency in either Java or Golang is required; experience with both is a strong plus.
Experience with modern frameworks such as Quarkus, Spring Boot, or equivalent in Golang is highly desirable.
Strong knowledge of object-oriented design principles and software design patterns.
Proficient in defining API specifications (OpenApi/Swagger, Rest, GraphQL, gRPC, WebSocket)
Experience with Kubernetes and container technologies
Proven experience in developing SaaS backend solutions based on micro services architecture in public clouds (aws, Azure, GCP)
Familiarity with several frameworks or Cloud services used in large scale distributed systems such as Kafka, Flink, RabbitMQ, Redis, Spark, Amazon Kinesis, Google Cloud Dataflow, Azure Event Hub
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