Backend Engineering Lead - Golang/Node.js (6-9 yrs)

We're seeking a seasoned Backend Engineering Lead to architect and scale our core services. You'll own the design, development, and operational excellence of microservices built in Go and Node.js, champion data modeling best practices (ERDs), and guide a team of high-performing engineers toward shipping robust, AI-enhanced features at scale

Responsibilities :

- Define and maintain service architecture in Go and Node.js, ensuring scalability, resilience, and low latency.

- Lead the creation and upkeep of comprehensive Entity-Relationship Diagrams (ERDs) and maintain an up-to-date data model library.

- Manage, mentor, and inspire a diverse team of 5-10 backend engineers (maverick talent), fostering collaboration, autonomy, and ownership.

- Conduct regular code reviews, design discussions, and performance feedback sessions.

- Collaborate with Data Science and ML engineers to integrate OpenAI models (e. g., GPT-4) for features like smart audio transcription, summarization, and recommendation.

- Work with DataStax (Cassandra) or similar NoSQL systems to power low-latency user analytics and AI inference pipelines.

- Establish and enforce best practices for CI/CD, automated testing, performance benchmarking, and observability (metrics, logs, tracing).

- Own SLA/SLOs and incident response processes, driving rapid root-cause analysis and post-mortems.

- Partner with Product, UX, and DevOps to translate business goals into technical roadmaps and deliver on tight timelines.

- Evangelize backend and data architecture decisions across the engineering organization.

Requirements :

- 6+ years of backend experience with Go and Node.js, building microservices in production.

- Deep understanding of RESTful APIs, gRPC, message queues (Kafka/RabbitMQ), and event-driven architectures.

- Proven ability to author and maintain ERD documents, relational and NoSQL schema design (PostgreSQL, DataStax Cassandra).

- 2+ years managing high-performance engineering teams, with a track record of growing and mentoring maverick engineers.

- Hands-on experience integrating AI/ML models, preferably OpenAI APIs or custom ML pipelines, into backend systems.

- Strong background in designing CI/CD pipelines (Jenkins/GitHub Actions), containerization (Docker/Kubernetes), and cloud services (AWS/GCP).

- Experience with GraphQL or real-time streaming architectures (WebSockets).

- Familiarity with large-language model fine-tuning and hosting on infrastructure like AWS SageMaker or Azure ML.

- Background in user-centric analytics and personalization algorithms.

- Open source contributions in Go or Node.js ecosystems.