Backend Engineer Lead

Key Responsibilities

1. Architect & Design

• ○ 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.

2. Team Leadership & Mentorship

• 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.

3. AI/ML Integration

• 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.

4. Delivery & Quality

• 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.

5. Cross-Functional Collaboration 

• 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.

Must-Have Qualifications

● Technical Expertise:

1. 6+ years backend experience with Go and Node.js, building microservices in production.
2. Deep understanding of RESTful APIs, gRPC, message queues (Kafka/RabbitMQ), and event-driven architectures.

• Data Modeling:

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

● Team Leadership:

1. 2+ years managing high-performance engineering teams, with a track record of growing and mentoring “maverick” engineers.

● AI/ML Integration:

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

● Operational Excellence:

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

Nice-to-Have

● 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.

What We Offer

● Competitive salary with performance bonuses and equity options.

● Flexible work hours and hybrid work policy.

● Generous learning & development budget for conferences, courses, and certifications.

● A culture that values creativity, ownership, and rapid experimentation.

● Opportunity to shape the future of audio social in India’s biggest emerging markets.