Staff Software Engineer developing backend components for Nirmata's AI platform in a hybrid setup. Collaborating on innovative solutions for cloud-native technology adoption.
Responsibilities
Collaborate with a team of engineers and product managers, while taking ownership of key areas of the Nirmata AI Platform from design to delivery.
Make meaningful contributions at the requirements, architecture, and design levels, and take responsibility for ensuring the platform can scale with the growth of our customer base.
Help define and drive the architecture and implementation of the data processing subsystems, ensuring it aligns with technical and business goals for the next two to five years.
Play a key role in the design and implementation of AI/ML features, from initial concept through production readiness.
Work closely with cross-functional teams to integrate features effectively and optimize system performance with a long-term perspective.
Participate in code reviews and take accountability for code quality, offering thoughtful, constructive feedback and upholding high standards.
Stay informed about the latest developments in software technologies, and bring forward ideas and improvements that drive product and team success.
Requirements
Bachelor's or Master's degree in Computer Science or a related field.
10+ years of professional experience in software development.
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)
Worked for a startup or similar environment handling large volumes of data and events (Datadog, New Relic, Splunk, Sysdig, …)
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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