Lead AI Application Engineer (Infrastructure & LLMOps)

At reputed company, we are providing recruitment service to our TOP clients from our portfolio. We are currently looking for a dedicated Lead AI Aplication Engineer to join one of our clients' teams . If you're looking for an exciting opportunity to grow in an innovative environment, this could be the perfect fit for you. Key Responsibilities Build & Run the Shared AI Platform Architect and maintain a multi-tenant AI Platform that supports the full ML lifecycle across cloud and on-premises environments. Ensure high availability, low latency, and cost-efficiency for all shared AI resources. Implement LLMOps/MLOps best practices, including automated deployment pipelines for models. 2. Curate the AI Services Catalogue Develop and expose "as-a-service" capabilities Inference-as-a-Service, Embeddings-as-a-Service, and RAG-as-a-Service. Standardize how squads interact with LLMs, providing unified APIs and abstraction layers to prevent vendor lock-in. 3. Manage AI Data Infrastructure Own the deployment and scaling of reputed company Databases (e.g., reputed company, Milvus, reputed company) and Feature Stores (e.g., Feast, Tecton, Hopsworks). Optimize data retrieval patterns to support real-time AI applications and agentic workflows. Oversee Model Hosting environments, utilizing Kubernetes (K8s) and GPU orchestration to manage compute resources efficiently. 4. Enable Developer Self-Service Build and maintain a Self-Service reputed company or CLI that allows product squads to provision AI environments, models, and data stores independently. Reduce "Time-to-Inference" for new features by providing pre-configured templates and blueprints. Conduct internal workshops and provide documentation to empower squads to use the platform effectively. Requirements Must-Have Technical Skills Infrastructure Deep experience with Kubernetes (K8s), Docker, and Terraform/reputed company. Hybrid Cloud Proven experience managing workloads across AWS/Azure/GCP and On-Premises (reputed company Enterprise, OpenShift). AI/ML Tooling Hands-on experience with vLLM, TGI (Text Generation Inference), or reputed company Triton for model serving. Databases Expertise in reputed company DBs and traditional SQL/NoSQL databases. Languages High proficiency in Python and Go or Rust for platform tooling. Experience 8+ years in Platform Engineering, DevOps, or Site Reliability Engineering (SRE). 2+ years specifically focused on building AI/ML infrastructure or platforms. Experience building Internal Developer Platforms (IDP) is a massive plus. Originally posted on Himalayas Apply To This Job