Senior GenAI & ML Engineer (Azure, LangChain)

Cognizant; Juneau (AK); On-site; USD 100,000 - 156,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

401(k) plan and contributions

Paid holidays and PTO

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant seeks a Senior AI/ML Engineer to design and deliver advanced analytics and AI-driven solutions for global investment banking and brokerage operations. The role combines ML, GenAI, and full stack development using Python, PySpark, and Azure ML.

You will collaborate with stakeholders to transform complex financial data into actionable insights, build scalable AI applications, and ensure governance and responsible AI practices across deployments.

Qualifications

• 8+ years of experience in Data Science, ML, AI Engineering.
• Expert-level proficiency in Python and PySpark.
• Strong experience with FastAPI, REST APIs, and microservices.
• Hands-on with LangChain, LangGraph, RAG, and Agentic AI frameworks.
• Experience deploying enterprise-grade AI/ML solutions in cloud environments.

Responsibilities

• Design, develop, and deploy advanced ML models for financial data.
• Build Generative AI solutions using Azure OpenAI Service.
• Develop enterprise-grade AI/ML pipelines and MLOps workflows.
• Collaborate with product and business stakeholders to translate needs into analytics.

Skills

Python

PySpark

Azure Machine Learning

Generative AI

Full Stack Development

LangChain

LangGraph

RAG

Agentic AI Frameworks

LLMs

Tools

FastAPI

REST APIs

Microservices Architecture

Docker

Kubernetes

Azure OpenAI Service

Azure Databricks

Azure Data Lake

Azure DevOps

Job description

Cognizant seeks a Senior AI/ML Engineer to design and deliver advanced analytics and AI-driven solutions for global investment banking and brokerage operations. The role combines ML, GenAI, and full stack development using Python, PySpark, and Azure ML.

You will collaborate with stakeholders to transform complex financial data into actionable insights, build scalable AI applications, and ensure governance and responsible AI practices across deployments.