Description
Responsibilities
GenAI Application Development
- Develop LLM-powered applications using Python-based frameworks.
- Implement RAG pipelines and vector database integrations.
- Build prompt orchestration workflows and response optimization logic.
Agentic Workflow Implementation
- Develop AI agents with tool integration capabilities.
- Implement reasoning loops, memory modules, and execution controls.
- Integrate AI agents into backend systems and APIs.
Deployment & Optimization
- Build REST APIs and microservices for AI applications.
- Optimize inference performance, latency, and cost.
- Support CI/CD pipelines and cloud deployments.
Testing & Quality
- Implement evaluation metrics for hallucination control and accuracy.
- Debug and resolve performance bottlenecks.
- Document code, workflows, and solution design.
Experience and Competency Requirements
- 4–8 years of software development experience.
- 2+ years working with AI/ML or GenAI applications.
- Robust proficiency in Python.
- Experience with LLM APIs, embeddings, and vector databases.
- Exposure to cloud-based deployments and containerization.
- Strong analytical and debugging capabilities.
- Should have decent to good experience in data handling and analytics with python
Skills
GenAI & LLM Frameworks (Mandatory)
- OpenAI APIs / Azure OpenAI
- LangChain / LangGraph / LlamaIndex
- Transformers (Hugging Face)
- Prompt engineering and evaluation frameworks
Agentic Systems & Orchestration
- Multi-agent design patterns (MCP, A2A, ReAct etc)
- Tool integrations and API orchestration
- Memory frameworks and contextual reasoning
- Guardrails, observability, and monitoring
Data & Infrastructure
- Vector databases (Pinecone, FAISS, Weaviate or equivalent)
- Python, FastAPI, REST services
- Docker, Kubernetes
- Cloud platforms (AWS, Azure, GCP)
Data Handling & Analytics Skills
- Data preprocessing and ETL for structured and unstructured data
- Data manipulation using Pandas, NumPy, and SQL
- Explora
📌 Project Manager (New Delhi)
🏢 EXL
📍 New Delhi