Senior AI/ML Engineer
Primary location: Bengaluru, Karnataka
INR 3700K-5000K (estimate) Senior-level Full Time
Tasks
- Build AI model serving inference orchestration
- Build AI platform for model development deployment serving
- Build automated CI CD pipelines for model and agent deployment
- Build distributed microservices backend for AI workloads
- Create self service AI deployment capabilities
- Design and implement generative AI solutions with LLM RAG vector search
- Design enterprise AI systems architecture
- Develop AI services APIs microservices
- Ensure responsible AI model governance security and compliance controls
- Establish MLOps LLMOps and agentic ops practices
- Establish observability logging monitoring distributed tracing alerting
- Implement caching asynchronous processing messaging and queuing
- Implement model lifecycle management and experiment tracking
- Implement monitoring and governance for AI applications models prompts agents
- Implement real-time and batch inference
- Integrate AI capabilities with enterprise APIs and applications
- Lead engineering standards best practices architecture patterns and mentorship
- Operationalize LLM RAG systems and AI agents
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Agentic AI | Alerting | Amazon Web Services | Asynchronous processing | Azure | Azure ML | CI/CD | Caching | Cloud Native | Cloud platform | Containers | Distributed Systems | Distributed tracing | Embeddings | Event Driven | Event-driven architecture | Generative AI | Google Cloud | Google Cloud Platform | Kubeflow | Kubernetes | LLMOps | Language Models | Large Language Models | Logging | MLOps | MLflow | Machine Learning | Messaging | Microservices | Model Governance | Monitoring | Observability | Prompts | Python | Queuing | RAG | Responsible AI | Retrieval-Augmented Generation | SageMaker | Vector Databases | Vector Search | Vertex AI | Web Services
Education
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