Project Manager

EXL Talent Acquisition Team; New Delhi; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

EXL Talent Acquisition Team in India seeks a seasoned GenAI/LLM engineer to design and build end-to-end AI applications in Python. You will work on RAG pipelines, vector databases, and prompt orchestration to deliver scalable solutions.

You will implement agentic workflows, integrate tools and APIs, and optimize deployment through REST services, Docker/Kubernetes, and cloud platforms. Strong Python and AI/ML experience required.

Qualifications

• 4–8 years of software development experience.
• 2+ years working with AI/ML or GenAI applications.
• Strong 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

Responsibilities

• Develop LLM-powered applications using Python-based frameworks.
• Implement RAG pipelines and vector database integrations.
• Build prompt orchestration workflows and response optimization logic.
• Develop AI agents with tool integration capabilities.
• Implement reasoning loops, memory modules, and execution controls.
• Integrate AI agents into backend systems and APIs.
• Build REST APIs and microservices for AI applications.
• Optimize inference performance, latency, and cost.
• Support CI/CD pipelines and cloud deployments.
• Implement evaluation metrics for hallucination control and accuracy.
• Debug and resolve performance bottlenecks.
• Document code, workflows, and solution design.

Skills

Python

AI/ML experience

LLM APIs

Embeddings

Vector databases

Cloud deployments

Docker

Kubernetes

REST APIs

Data handling

Tools

OpenAI API

Azure OpenAI

LangChain

LangGraph

LlamaIndex

Transformers (Hugging Face)

Job 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.
• Strong 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
• Exploratory data analysis (EDA) and statistical analysis
• Data visualization (Matplotlib, Seaborn, Plotly, Tableau, Power BI)