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.
Robust analytical and debugging capabilities.
Should have decent to positive 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
Explorator

📌 Project Manager New Delhi
🏢 EXL
📍 New Delhi