Data Scientist 2

Job Overview
Do you enjoy building modern Analytics, AI, and Generative AI solutions using cutting-edge cloud technologies? Are you 
passionate about developing intelligent applications, AI agents, enterprise integrations, and scalable cloud-native 
services?
Conduent is seeking an AI Solutions Engineer with strong software engineering, cloud development, and Generative AI 
expertise to join our Analytics & Data Science Practice. This role is responsible for designing, developing, deploying, and 
supporting enterprise Analytics, AI, and GenAI solutions leveraging Azure AI services and modern cloud-native 
technologies. The engineer will work closely with Senior Engineers, Technical Leads, Data Scientists, and Architects to 
build reusable platform capabilities and deliver innovative solutions across multiple business domains.
The role combines hands-on software engineering, AI application development, cloud deployment, and DevOps practices 
to create secure, scalable, and production-ready AI solutions. Success in this role is measured by the ability to rapidly 
develop, deploy, and operationalize high-quality Analytics and AI solutions while contributing reusable capabilities that 
accelerate future delivery.

Responsibilities:

• Develop, test, and deploy Analytics, AI, and Generative AI solutions using Azure AI services and modern 

application development frameworks.

• Build GenAI applications leveraging Azure AI Foundry, Azure OpenAI, Azure AI Search, & related Azure services.

• Develop Retrieval-Augmented Generation (RAG) solutions, AI assistants, AI agents, knowledge retrieval systems, 

and intelligent business applications.

• Implement prompt engineering, prompt orchestration, and grounding

• Develop AI agents, agent workflows, & multi-step reasoning processes to automate tasks and user interactions.

• Implement tool integrations, workflow orchestration, and human-in-the-loop capabilities.

• Design and develop APIs, microservices, integrations, and cloud-native services.

• Deploy, configure, and support solutions across Azure cloud environments.

• Develop and maintain infrastructure, application configurations, & deployment assets supporting solution delivery.

• Perform unit testing, integration testing, debugging, and performance optimization.

• Build and maintain CI/CD pipelines supporting automated testing and deployment.

• Work with Azure services including App Services, Azure Functions, Container Apps, Storage, Key Vault, API 

Management, and related platform components.

• Support production deployments, release validation, and operational readiness activities.

• Follow established development standards, architecture guidelines, DevOps practices, and coding standards.

• Participate in code reviews, design reviews and contribute to technical documentation, implementation guides, 

deployment procedures, and operational runbooks.

• Participate in Agile planning, sprint execution, estimation, and delivery activities.

• Stay current with advances in AI, GenAI, cloud technologies, and software engineering practices.

Experience Needed:

• 5-8 years of experience in software engineering, cloud engineering, analytics, AI, data engineering, or application 

development.

• 3+ years experience developing and delivering cloud-native applications and services. Hands-on Azure experience 

is required.

• Experience delivering enterprise solutions using modern software development practices.

• Experience working within Agile and cross-functional delivery teams.

• Hands-on expertise to develop and deploy applications on Azure, including services such as App Service, Azure 

Functions, Container Apps, Azure AI Foundry, AKS, Storage, Key Vault, API Management, or similar components

• Hands-on experience delivering GenAI solutions into production environments including prompt and RAG (retrieval[1]augmented generation) patterns, responsible AI controls & guardrails, AI orchestration.

• Strong Python development skills.

• Experience building REST APIs, microservices and implementing cloud-native applications.

• Strong understanding of software architecture principles and design patterns.

• Experience building containerized applications using Docker and Kubernetes technologies.

• Familiarity with front-end application development and modern application frameworks.

• Experience with: CI/CD pipelines, Infrastructure-as-Code, Test automation, Monitoring and observability, 

Production support processes, Root cause analysis and Performance optimization

• BS or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical discipline.

Additional Requirements

• Strong written and verbal communication skills.

• Ability to work directly with technical and business stakeholders.

• Experience supporting global onshore/offshore delivery models.

• Strong problem-solving and analytical skills.

• Ability to balance hands-on development responsibilities with technical leadership responsibilities.

• Passion for emerging Analytics, AI, and GenAI technologies