AI Software Engineer at Genia enhancing productivity through AI implementations. Responsible for developing scalable solutions in data, AI, and BI workflows.
About the role
- 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
- Prior experience using AI/ML technologies (LLM, SML, RAG, Prompt Engineering, …)
- Contribution to OpenSource projects is a plus, showcasing your engagement with the developer community.
Benefits
- Comprehensive health coverage including medical, dental, and vision; Equity awards; Flexible time off
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