We are seeking a Senior AI Developer who combines strong backend engineering expertise with deep knowledge of AI systems. The ideal candidate will have hands-on experience in designing, deploying, and scaling AI-powered applications in real-world production environments.

This role involves working on system architecture, data pipelines, APIs, model serving, and monitoring frameworks. You will collaborate with cross-functional teams to ensure scalable, robust, and efficient AI deployments, while also mentoring junior engineers and promoting best practices in engineering excellence.

Key Responsibilities

- Design and lead the development of scalable AI architectures with a focus on backend robustness and system orchestration.

- Build and maintain modular AI pipelines, including data preprocessing, training, model serving, and monitoring.

- Develop APIs, microservices, and backend logic to enable seamless AI model integration and real-time inference.

- Collaborate with DevOps and infrastructure teams to deploy AI solutions across cloud, hybrid, and edge environments.

- Ensure code quality and maintainability through CI/CD pipelines, version control, and containerization.

- Optimize system performance, including profiling, parallelization, and GPU/edge deployment strategies.

- Implement best practices for model reproducibility, observability, and governance using tools like MLflow, Prometheus, or Grafana.

- Mentor junior team members in scalable AI system design and backend engineering practices.

Must-Have Skills :

- Strong programming skills in Python (Go or Rust experience is a plus).

- Proficiency in backend frameworks such as FastAPI, Flask, or gRPC.

- Solid understanding of AI system architecture and lifecycle management.

- Experience with Docker, Kubernetes, and CI/CD for production ML deployments.

- Knowledge of distributed systems, asynchronous processing, and real-time API design.

- Familiarity with MLflow, DVC, or Weights & Biases for model tracking/versioning.

- Hands-on experience with Linux environments and containerized AI workflows.

Good to Have :

- Experience in computer vision (e.g., YOLO, UNet, transformers).

- Knowledge of streaming inference systems like DeepStream or Kafka.

- Exposure to edge AI hardware (Jetson, Coral) and inference optimization (ONNX, TensorRT).

- Familiarity with cloud platforms (AWS, GCP, Azure).

- Experience with data augmentation, synthetic data, or simulation tools.

- Contributions to open-source or research publications in AI/ML infrastructure.

Qualifications :

- B.E./B.Tech/M.Tech in Computer Science, Software Engineering, or related field.

- 5+ years of professional experience in software engineering, ideally within AI/ML product companies.

- Proven track record in designing and deploying production-grade AI systems.

Why Join Us?

- Work on cutting-edge AI infrastructures with real-world applications.

- Collaborate with a talented, mission-driven team in a fast-paced environment.

- Gain hands-on exposure to advanced hardware and scalable system design.

- Opportunity to take ownership of systems end-to-end from architecture to deployment.