GSNA Education - Technical Lead - Backend Architecture

About the Role :

We're looking for a Tech Lead (Backend) with a strong foundation in backend architecture and hands-on experience integrating AI/ML capabilities into scalable systems.

As the Backend Tech Lead, you'll guide the technical direction of our backend services and AI-driven features, working closely with cross-functional teams to design, build, and deploy systems that support intelligent, data-driven products.

You'll combine leadership with deep technical expertise to drive backend innovation, mentor developers, and ensure our systems remain reliable, efficient, and scalable.

Key Responsibilities :

- Lead Backend Development : Architect, develop, and maintain high-performance, scalable backend systems.

- AI/ML Integration : Collaborate with data science and ML engineers to productionize models, build APIs, and deploy AI features into live environments.

- Team Leadership : Mentor backend engineers, perform code reviews, and foster a culture of high-quality engineering and continuous learning.

- System Design : Make key decisions on architecture, technology stack, and infrastructure (e.g., microservices, event-driven systems, containerization).

- Scalability & Performance : Ensure backend systems can scale efficiently to support AI-driven workloads and real-time applications.

- Collaboration : Work closely with Product, DevOps, Frontend, and AI teams to deliver seamless end-to-end solutions.

- Tech Strategy : Evaluate new tools and technologies (e.g., LLMs, vector databases, inference services) and propose solutions that improve backend capabilities.

- Security & Compliance : Implement best practices around data security, privacy, and API access management.

Requirements :

Must-Have :

- 6+ years of experience in backend development with at least 2 years in a technical leadership or lead engineer role.

- Strong programming skills in languages like Python, Go, Java, or Node.js.

- Experience building RESTful APIs, GraphQL, and microservices architectures.

- Practical experience integrating AI/ML models into production (e.g., using TensorFlow, PyTorch, Hugging Face, or similar).

- Experience with databases (SQL and NoSQL) and caching systems (Redis, Memcached).

- Familiarity with cloud platforms (AWS, GCP, or Azure), containerization (Docker), and orchestration tools (Kubernetes).

- Understanding of model inference, feature engineering, and ML pipeline deployment.

- Strong communication and stakeholder management skills.

Nice-to-Have :

- Experience with LLMs, embedding models, or vector search (e.g., using FAISS, Pinecone, Weaviate).

- Knowledge of real-time data streaming (Kafka, Apache Flink, etc.

- Familiarity with MLOps tools like MLflow, Sagemaker, or Kubeflow.

- Exposure to data privacy frameworks and secure data handling.

Why Join Us?

- Work on cutting-edge AI/ML products that impact [industry, e.g., healthcare, finance, education].

- Be part of a collaborative, fast-paced, and growth-oriented team.

- Opportunity to lead the backend strategy and influence the AI roadmap.

- Competitive compensation, equity options, and great benefits.