GenAI Lead Engineer — Azure ML & LangChain Innovator

Cognizant; Providence (RI); On-site; USD 100,000 - 156,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays plus Paid Time Off

401(k) plan and contributions

Long-term/Short-term Disability

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant is seeking a Senior AI/ML Engineer to design and deliver analytics and AI-driven solutions for investment banking. You will work with Python, PySpark, LangChain, LangGraph and GenAI on enterprise platforms, building scalable ML models and GenAI apps.

Responsibilities include developing full stack services with FastAPI, applying MLOps practices, and ensuring governance and security across Azure-based deployments. Strong collaboration with stakeholders is required.

Qualifications

• 8+ years in Data Science, ML, or AI engineering.
• Expert Python and PySpark for large-scale data processing.
• Hands-on with LangChain, LangGraph, RAG, and Agentic AI frameworks.
• Experience deploying enterprise AI solutions in cloud envs (Azure).

Responsibilities

• Design, develop, and deploy ML models on large financial datasets.
• Build predictive and anomaly-detection models with rigorous validation.
• Create Generative AI solutions using Azure OpenAI Service and GenAI frameworks.
• Develop FastAPI backends and microservices integrating ML components.
• Establish model monitoring, governance, and lifecycle management.

Skills

Python

PySpark

LangChain

LangGraph

RAG

Agentic AI Frameworks

LLM Application Development

FastAPI

REST APIs

Microservices

OOP

Software Engineering Best Practices

NLP

Time-Series Forecasting

Tools

Azure Machine Learning

Azure OpenAI Service

Azure Databricks

Azure Data Lake

Azure DevOps

Docker

Kubernetes

CI/CD

Job description

Cognizant is seeking a Senior AI/ML Engineer to design and deliver analytics and AI-driven solutions for investment banking. You will work with Python, PySpark, LangChain, LangGraph and GenAI on enterprise platforms, building scalable ML models and GenAI apps.

Responsibilities include developing full stack services with FastAPI, applying MLOps practices, and ensuring governance and security across Azure-based deployments. Strong collaboration with stakeholders is required.