AI/ML Developer

AI/ML Engineer – Generative AI Platforms (Remote)

About Cognizant

Cognizant is one of the world’s leading professional services companies, helping clients modernize technology, reimagine processes, and transform experiences. We engineer modern businesses to improve everyday life. Our associates around the globe help clients build stronger, more agile, and innovative organizations.

Our AI and Digital Engineering practice helps clients unlock value through Artificial Intelligence, Machine Learning, Intelligent Automation, Cloud Transformation, and Data Modernization. We partner with global enterprises to build scalable AI-powered solutions that accelerate innovation, improve productivity, and drive business outcomes.

Role Overview

Cognizant is seeking an experienced AI/ML Engineer – Generative AI Platforms to join our growing AI Engineering team.

This is a hands-on engineering role focused on designing, developing, deploying, and supporting AI-powered Document Processing and AI Authoring platforms. The ideal candidate will have deep experience building enterprise Generative AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Intelligent Document Processing (IDP), semantic search, and cloud-native AI architectures.

You will collaborate with Solution Architects, Product Owners, Data Engineers, and Software Engineering teams to develop innovative AI solutions that deliver scalable, secure, and production-ready business capabilities.

Work Model

This position is fully remote within the United States, providing the flexibility to work from home while collaborating with global teams across multiple locations and time zones.

Occasional travel may be required for client meetings, planning sessions, team collaboration events, and strategic initiatives.

Key Responsibilities

Generative AI Solution Development

• Design, develop, and deploy enterprise-grade Generative AI solutions using Large Language Models (LLMs).
• Build intelligent document processing and AI-assisted authoring capabilities supporting complex business workflows.
• Develop and optimize Retrieval-Augmented Generation (RAG) architectures to enhance response quality and contextual relevance.
• Implement prompt engineering strategies to improve AI performance, accuracy, and reliability.
• Collaborate with product and business teams to translate business requirements into scalable AI solutions.

Document Intelligence & AI Authoring

• Develop capabilities for:
  • Document Extraction
  • Document Classification
  • Data Validation
  • Knowledge Retrieval
  • AI-Assisted Content Generation
• Design workflows that automate document understanding and content creation processes.
• Build validation frameworks that improve accuracy, traceability, and confidence in AI-generated outputs.
• Support end-to-end lifecycle management of AI-powered document solutions.

RAG, Semantic Search & Knowledge Retrieval

• Design and optimize embedding strategies for enterprise data and document repositories.
• Implement vector search and semantic retrieval solutions to improve knowledge discovery.
• Develop grounding mechanisms that ensure AI responses are accurate, contextual, and explainable.
• Build and maintain retrieval pipelines that support high-performance search and content generation capabilities.
• Evaluate and enhance retrieval effectiveness using modern AI evaluation methodologies.

API & Microservices Development

• Design and develop APIs and microservices using Python and FastAPI.
• Build scalable and reusable backend services supporting AI applications and integrations.
• Develop secure API-based connections between AI platforms, enterprise systems, and third-party applications.
• Support microservice deployment, monitoring, maintenance, and optimization activities.

AWS Cloud & AI Platform Engineering

• Build and support cloud-native AI solutions leveraging AWS services.
• Develop and maintain solutions utilizing:
  • AWS Bedrock
  • AWS Lambda
  • Amazon S3
  • Amazon RDS
  • Related AWS services
• Implement scalable, secure, and highly available cloud architectures for AI workloads.
• Collaborate with cloud and platform engineering teams to optimize performance and cost efficiency.

Testing, Quality & Operational Excellence

• Create and execute:
  • Functional Tests
  • Integration Tests
  • AI Quality Validation Tests …