Security engineer, detection and response
Writer
CloudDistributed SystemsPython
Salary
💰 ₹300,000 - ₹1,000,000 per year
Job Level
Senior
About the role
- Architect scalable AI systems: design and implement production-grade architectures emphasizing backend services, orchestration, and automation.
- Build end-to-end pipelines: develop modular pipelines for data ingestion, preprocessing, training, serving, and continuous monitoring.
- Develop APIs & services: build APIs, microservices, and backend logic to integrate AI models into real-time applications.
- Operationalize AI: collaborate with DevOps and infrastructure teams to deploy models across cloud, hybrid, and edge environments.
- Enable reliability & observability: implement CI/CD, containerization, and monitoring tools to ensure robust and reproducible deployments.
- Optimize performance: apply profiling, parallelization, and hardware-aware optimizations for efficient training and inference.
- Mentor & guide: support junior engineers by sharing best practices in AI engineering and backend system design.
Requirements
- 5+ years of software engineering experience, ideally in AI/ML-driven products.
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field.
- Strong backend development experience in Python (bonus: Go, Rust, or Node.js).
- Hands-on experience with FastAPI, Flask, or gRPC for building high-performance services.
- Deep understanding of model development workflows (data processing → training → deployment → monitoring).
- Strong grasp of distributed systems, Kubernetes, Docker, CI/CD pipelines, and real-time data processing.
- Experience with MLflow, DVC, Weights & Biases, or similar experiment-tracking/reproducibility platforms.
- Comfort with Linux, containerized deployments, and major cloud providers (AWS, GCP, or Azure).
- Experience mentoring or guiding junior engineers.
- Nice-to-have: experience with computer vision models (YOLO, UNet, transformers); streaming inference systems (Kafka, NVIDIA DeepStream); edge AI hardware (NVIDIA Jetson, Coral) and optimizations (TensorRT, ONNX); synthetic data generation or augmentation; open-source contributions or research publications in AI/ML systems.
