Lead hands-on design and development of analytics, AI, and GenAI platforms and services
Establish reusable reference architectures, design patterns, and architectural guardrails
Define Responsible AI, security, privacy, and model lifecycle governance controls
Support solution sizing, proposals, and client discussions
Mentor engineers, technical leads, and architects
From the employer’s posting
Lead hands-on design and development of analytics, AI, and GenAI platforms, solutions, and services.
Establish reusable reference architectures, design patterns, standards, and architectural guardrails.
Define Responsible AI, security, privacy, observability, model lifecycle management, and operational governance controls.
Support solution sizing, proposals, client discussions, and technology modernization initiatives.
Mentor engineers, technical leads, and architects while driving adoption of engineering best practices and development standards.
Education & alternatives
- Advanced knowledge of computer science, software engineering, software development methodologies, and modern application architecture practices.
- BS or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical discipline.
Additional Requirements
Open 4 monthsWe first saw this posting 126 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
Status in our records
Live
First seen by us
Jul 10, 2026126 days ago
Recorded sightings
497
Last seen by us
Nov 13, 2026
Jul 10, 2026today
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 126
477
Up longer than most. Similar jobs usually come down between day 4 and day 77.
Well past Conduent’s usual: its jobs come down by about day 37.
From 51 similar postings that came down, and 29 of Conduent’s. Coming down is not always a hire.
Conduent is hiring
8 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
SQL
Azure
Where the posting names them
- Experience leading cross-functional engineering teams and large-scale technical initiatives
- Experience in full stack development, design, architecture, implementation, and deployment using Python and cloud container services to deliver scalable, secure, and maintainable applications. • Understand the operational dependencies across applications, networks, systems, security, and policies in both on-premises and cloud environments, including VMs, networking, VPN/ExpressRoute, Microsoft Entra, and Azure Storage.
- • Proficiency in Storage, Relational Databases, Cloud Databases, DocumentDB/No-SQL , MPP’s, Model Data Transformation technology design and implementation.
- Experience in full stack development, design, architecture, implementation, and deployment using Python and cloud container services to deliver scalable, secure, and maintainable applications. • Understand the operational dependencies across applications, networks, systems, security, and policies in both on-premises and cloud environments, including VMs, networking, VPN/ExpressRoute, Microsoft Entra, and Azure Storage.
- • Proficiency in Storage, Relational Databases, Cloud Databases, DocumentDB/No-SQL , MPP’s, Model Data Transformation technology design and implementation.
- Demonstrate experience as an architect delivering modern data architecture platforms and solutions across data lake, lakehouse, data integration, governance, and analytics capabilities.
Experience Needed:
- • 15+ years of industry experience, including at least 5 years of experience as lead architect designing and building cloud-native analytics and AI / GenAI solutions. Hands-on Azure experience is required.
- • Hands-on experience delivering GenAI solutions into production environments including designing and governing enterprise AI architectures, prompt and RAG (retrieval-augmented generation) patterns, responsible AI controls & guardrails, AI orchestration, AI/ML model lifecycle management, and secure integration of AI capabilities into analytics and enterprise applications.
- • Hands-on experience delivering GenAI solutions into production environments including designing and governing enterprise AI architectures, prompt and RAG (retrieval-augmented generation) patterns, responsible AI controls & guardrails, AI orchestration, AI/ML model lifecycle management, and secure integration of AI capabilities into analytics and enterprise applications.
- 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
- Experience leading cross-functional engineering teams and large-scale technical initiatives
Additional Requirements
- Good to have architectural and implementation knowledge of Microsoft Fabric, OneLake, Fabric Pipelines, Medallion Architecture, Fabric Data Agent, and Azure AI Foundry.
- Demonstrate a track record of successfully completing complex technical projects.
About 51,000 in 2025, down 9% from the year before.Annual report (SEC Form 10-K)
Company
Listed as CNDT.
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Do you enjoy building enterprise-grade platforms and analytics & AI solutions? Do you want to establish and lead an enterprise-grade platform that drives Analytics & AI solutions across multiple domains?
Conduent is seeking an Analytics & AI Solution Architect with cloud, data, analytics, and GenAI expertise to join our Analytics & Data Science Practice. This role requires broad technical depth and will support defining reference architectures, governing solution design decisions, enabling reusable platform capabilities, ensuring alignment with enterprise technology standards, and driving adoption of modern AI technologies across Conduent businesses. The architect partners closely with business stakeholders, product leaders, engineering teams, and clients to translate business objectives into scalable, secure, and operationally sustainable solutions.
Responsibilities:
Lead hands-on design and development of analytics, AI, and GenAI platforms, solutions, and services.
Establish reusable reference architectures, design patterns, standards, and architectural guardrails. • Support design and governance of enterprise GenAI capabilities including RAG, Agentic AI, multi-agent orchestration, prompt frameworks, knowledge management, and evaluation frameworks.
• Define Responsible AI, security, privacy, observability, model lifecycle management, and operational governance controls.
Lead architecture, design, and implementation decisions across cloud-native applications, APIs, integrations, data platforms, containers, and DevOps pipelines. • Champion AI architecture strategy across data, model, application, and cloud infrastructure layers, including Generative AI, AI/ML platforms, model governance, responsible AI, security, observability, and scalable production deployment patterns.
Provide architecture leadership across multiple concurrent initiatives and work with delivery teams through implementation and production deployment.
Support solution sizing, proposals, client discussions, and technology modernization initiatives.
Mentor engineers, technical leads, and architects while driving adoption of engineering best practices and development standards.
Design and implement products and platforms that comply with the standards and best practices across multiple businesses & domains. Support architecture reviews & alignment with enterprise architecture and governance standards.
Drive the design, sizing, setup, and optimization of cloud environments and related services.
Advise on emerging technology trends and recommend adoption opportunities to maintain competitive advantage.
Experience Needed:
• 15+ years of industry experience, including at least 5 years of experience as lead architect designing and building cloud-native analytics and AI / GenAI solutions. Hands-on Azure experience is required.
• Hands-on experience delivering GenAI solutions into production environments including designing and governing enterprise AI architectures, prompt and RAG (retrieval-augmented generation) patterns, responsible AI controls & guardrails, AI orchestration, AI/ML model lifecycle management, and secure integration of AI capabilities into analytics and enterprise applications.
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
Experience leading cross-functional engineering teams and large-scale technical initiatives
Experience in full stack development, design, architecture, implementation, and deployment using Python and cloud container services to deliver scalable, secure, and maintainable applications. • Understand the operational dependencies across applications, networks, systems, security, and policies in both on-premises and cloud environments, including VMs, networking, VPN/ExpressRoute, Microsoft Entra, and Azure Storage.
• Proficiency in Storage, Relational Databases, Cloud Databases, DocumentDB/No-SQL , MPP’s, Model Data Transformation technology design and implementation.
Demonstrate experience as an architect delivering modern data architecture platforms and solutions across data lake, lakehouse, data integration, governance, and analytics capabilities.
Demonstrate experience with DevOps or equivalent industry-standard tools.
Constantly strive to research and improve the GenAI architecture inline with technology and framework advencements and enhance the product landscape.
Advanced knowledge of computer science, software engineering, software development methodologies, and modern application architecture practices.
BS or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical discipline.
Additional Requirements
Good to have architectural and implementation knowledge of Microsoft Fabric, OneLake, Fabric Pipelines, Medallion Architecture, Fabric Data Agent, and Azure AI Foundry.
Demonstrate a track record of successfully completing complex technical projects.
Deliver applications leveraging global delivery model.
Demonstrate professionalism and strong stakeholder engagement across clients, colleagues, and delivery teams.
Make sound, far-reaching technical decisions independently and take full responsibility for outcomes.
Communicate effectively and persuasively through strong written and verbal communication skills. • Gather end-user requirements and produce clear technical documentation.
• Manage competing priorities effectively and deliver high-quality outcomes with aggressive time-to-market timelines.