Senior Al Engineer - India

Job Description: Senior AI Engineer This role is Office Based, Hyderabad Office We are seeking an enthusiastic Senior AI Engineer to join our team and contribute to the development of intelligent talent technology. This is a hands-on opportunity for those early in their career to gain experience with AI and machine learning in a real-world, enterprise SaaS environment. You’ll work alongside experienced engineers and learn how large language models, recommender systems, and other AI solutions enhance the workplace. In this role you will… Inference Runtime Optimization: Architect, optimize, and maintain high-performance, asynchronous orchestration layers (FastAPI) integrated with advanced inference servers (vLLM, Triton Inference Server) to host and serve open-source models efficiently. Intelligent Routing Caching: Build and maintain an advanced semantic caching layer and dynamic routing engine that evaluates inbound prompts and dispatches them to the most cost-effective or lowest-latency model (managed services vs. self-hosted) based on intent and token volume. Multi-Region Cluster Management: Operationalize and maintain consistent deployments across three primary geographical regions, managing asymmetrical environment topologies (single-region Dev environments vs. globally distributed production clusters). Platform Observability Governance: Implement enterprise-grade rate-limiting, secure payload routing, and advanced telemetry dashboards using Prometheus and Grafana to track token consumption, error rates, and custom system metrics for internal departmental chargebacks. You’ve got what it takes if you have… Bachelors or Master Degree in Computer Science , or a related field. 6–8 years in backend platform engineering, systems architecture, or MLOps/LLMOps infrastructure design. Backend Stack : Expert-level Python with deep experience in concurrent/asynchronous programming patterns (FastAPI, Asyncio). AI/LLM Infrastructure : Hands-on experience with AWS Bedrock, prompt/model routing architectures, embedding generation, and hosting/serving open-source models from Hugging Face . Cloud DevOps : Proficient with core AWS services (EKS, IAM, VPC), containerization (Docker, Kubernetes), #LI-Onsite