Job Description :
We are looking for a Lead Backend Engineer to define and drive the backend architecture of our products. This role involves designing scalable and reliable systems, mentoring a team of backend engineers, and collaborating with cross-functional teams to deliver high-quality software. You will also contribute to integrating AI / ML capabilities into backend services and ensuring operational excellence through automation, observability, and strong engineering practices.
Core Responsibilities and Design :
- Define and maintain service architecture in Go and Node.js, focusing on scalability, resilience, and low latency.
- Create and maintain Entity-Relationship Diagrams (ERDs) and ensure data models are up to date.
Team Leadership and Mentorship :
Manage and mentor a team of 5- 10 backend engineers, promoting collaboration and accountability.Conduct regular code reviews, design discussions, and provide performance feedback.AI / ML Integration :
Collaborate with Data Science and ML engineers to integrate AI / ML models (e.g., GPT-4) for features such as transcription, summarization, and recommendations.Work with NoSQL systems like DataStax Cassandra to support analytics and AI inference and Quality :Implement best practices for CI / CD, automated testing, performance benchmarking, and observability (metrics, logs, tracing).Own SLA / SLOs, manage incident response, and lead root-cause analysis and Collaboration :Partner with Product, UX, and DevOps teams to translate business requirements into technical roadmaps.Communicate backend and data architecture decisions across the engineering organization.Requirements :
Experience : 6+ years of backend development with Go and Node.js, building and maintainingmicroservices in production.
System Design : Strong understanding of RESTful APIs, gRPC, event-driven architectures, and message queues (Kafka, RabbitMQ).Data Modeling : Experience with ERDs, relational schema design (PostgreSQL), and NoSQL databases (Cassandra or similar).Team Leadership : 2+ years of experience managing engineering teams, with a focus on mentoring and growing talent.AI / ML Integration : Hands-on experience integrating AI / ML models or APIs into backend systems.Operational Excellence : Proficiency in CI / CD (Jenkins, GitHub Actions), containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP).Nice-to-Have :
Experience with GraphQL or real-time streaming (WebSockets).Familiarity with ML model fine-tuning and hosting (AWS SageMaker, Azure ML).Knowledge of user analytics and personalization algorithms.Open-source contributions in Go or Node.js.(ref : hirist.tech)