Lead AI Engineer (Agentic Systems)
INR 3264K-4800K (estimate) Senior-level Full Time
Tasks
- Architect agentic systems
- Build agent data pipelines
- Build evaluation and reliability pipelines
- Build multi-agent workflows
- Create human-in-the-loop workflows
- Define code quality standards and PR review processes
- Define technical roadmap for agentic architecture
- Deploy agentic workloads with Docker and Kubernetes
- Design tool interfaces using MCP
- Engineer state management and orchestration
- Establish testing standards for non deterministic outputs
- Implement LLM observability and tracing
- Implement agent to agent communication
- Implement real time context injection
- Implement safety and control frameworks
- Integrate and optimize LLM models
- Optimize context windows and inference cost
- Prototype emerging agent tools and reasoning models
- Translate agent requirements into data schemas
Perks/Benefits
- N/A
Skills/Tech-stack
API Design | AWS | AWS Neptune | Asynchronous programming | Autogen | Azure | CI/CD | CrewAI | Databricks | Docker | DynamoDB | Embeddings | Evaluation Pipelines | GCP | Graph Databases | Graph Machine Learning | Hallucination detection | Knowledge graphs | Kubernetes | LLMOps | Langchain | Langfuse | Langgraph | Language Processing | Latency optimization | Litellm | MCP | Machine Learning | Natural Language | Natural Language Processing | Neo4j | NoSQL | Pinecone | PostgreSQL | Prompt engineering | Python | Qdrant | RAG | Retrieval architectures | Snowflake | Store optimization | Token Monitoring | Vector Databases | Vector Store | Vector Store Optimization | Weaviate
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI Engineer | Engineer | Lead | Lead AI | Lead AI Engineer | Learning Engineer | Machine Learning Engineer
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