Backend Engineering Lead - Node.js/TypeScript

Description :

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 modelling best practices, and guide a team of high-performing engineers toward shipping robust, AI-enhanced features at scale.

Responsibilities :

- Design and build scalable, low-latency microservices using Node.js (TypeScript) and Golang.

- Develop and maintain GraphQL APIs and backend integrations.

- Lead implementation of data flows and service logic in a distributed microservices

environment.

- Take ownership of cloud infrastructure setup, deployment workflows, and monitoring.

- Ensure system reliability, performance, and uptime by proactively addressing architectural

and operational concerns.

- Drive the integration of AI/ML capabilities such as transcription, summarisation, and

recommendations into the product.

- Own the full pipeline for AI features from embedding generation to querying vector databases alongside backend responsibilities.

- Design and manage efficient data models across relational, key-value, and unstructured data

stores.

- Ensure data scalability, consistency, and integrity across all systems.

- Work closely with fellow backend engineers to ship high-impact features rapidly and reliably.

- Contribute to technical direction, code reviews, best practices, and team-level decision-

making.

- Play an active role in hiring, onboarding, and mentoring engineers as the team grows.

Requirements :

- 5+ years of hands-on experience building and maintaining backend systems in production.

- Strong proficiency in at least two backend languages, including Node.js (TypeScript) and Golang (both are must-haves).

- Strong experience building and maintaining GraphQL and/or REST APIs.

- Proven experience running production environments on AWS, GCP, or Azure.

- Experience with deploying and managing containerised services (e. g., using ECS, Kubernetes,

or similar).

- Familiarity with CI/CD pipelines, automated testing, monitoring, and observability tools.

- Solid understanding of SQL and NoSQL databases (e. g., PostgreSQL, DynamoDB).

- Experience working with Redis and other in-memory data stores.

- Hands-on experience with message queues and pub/sub systems (e. g., RabbitMQ, Kafka).

- Exposure to vector databases, embeddings, and running AI/ML models in production.

- Experience working closely with mobile frontend teams, ensuring efficient APIs, performance

optimization, and debugging.

- Familiarity with Graph databases (e. g., Neptune, Neo4j).

- Experience building consumer-facing products at scale.

- Prior work with microservices architectures and distributed systems.

- Contributions to open-source projects or active technical blogging.

- Familiarity with large-language model fine-tuning and hosting on infrastructure like AWS

SageMaker or Azure ML.

- Background in user-centric analytics and personalisation algorithms.