Data Scientist 3

Job Overview

Do you enjoy deep hands-on development and leading other developers in to build modern Analytics, AI, and Generative AI technologies and solutions? Do you enjoy mentoring engineers, driving technical excellence, and delivering complex enterprise solutions?

Conduent is seeking a Senior AI Solutions Engineer / Technical Lead with strong cloud, application development, data, analytics, and Generative AI expertise to join our Analytics & Data Science Practice.This role serves as the senior developer for Analytics, AI, and GenAI solution delivery initiatives. The individual will lead technical implementation, and ensure engineering best practices are consistently applied across projects. The role combines hands-on technical leadership with responsibility for solution quality, delivery execution, engineering standards, and mentoring of junior engineers. Success in this role is measured by the ability to successfully deliver complex Analytics and AI solutions through technical leadership, team enablement, and disciplined engineering execution.

Responsibilities:
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Lead technical implementation and delivery of Analytics, AI, and GenAI solutions across multiple projects.
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Lead design and development of GenAI applications leveraging Azure AI Foundry, Azure OpenAI, Azure AI Search, and related Azure services.
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Design and implement Retrieval Augmented Generation (RAG) solutions, agent-based workflows, prompt orchestration frameworks, and AI-enabled business applications.
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Build scalable APIs, services, integrations, and cloud-native applications supporting AI solutions.
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Implement application security, observability, monitoring, testing, and operational readiness capabilities.
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Translate architecture, & functional requirements into detailed technical designs and implementation plans.
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Partner with Architects and Product Leaders to ensure solutions align with enterprise architecture standards and platform capabilities.
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Establish and enforce development standards, coding practices, testing standards, and deployment processes.
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Conduct code reviews and technical quality assessments.
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Ensure solutions meet scalability, performance, security, maintainability, and reliability requirements.
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Support production readiness reviews, deployment planning, operational handoff, and incident resolution activities.
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Participate in architecture reviews and contribute to reusable platform capabilities and accelerators.
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Promote adoption of reusable frameworks, components, development patterns, and DevOps practices.
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Guide engineers on architecture patterns, coding practices, cloud technologies, GenAI development, and troubleshooting approaches.
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Mentor junior engineers and support onboarding and development of new team members.
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Assist in technical interviews and candidate evaluations.
 

Experience Needed:
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10+ years of experience in software engineering, cloud engineering, analytics, AI, data engineering, or application development.
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3+ years leading technical delivery teams or serving as a technical lead on enterprise projects developing and delivering cloud-native applications and services. Hands-on Azure experience is required.
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Experience delivering enterprise Analytics, AI, or GenAI solutions into production environments.
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Experience working in Agile delivery environments and cross-functional teams.
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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
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Hands-on experience delivering GenAI solutions into production environments including 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.
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Strong Python development skills.
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Experience building REST APIs, microservices and implementing cloud-native applications.
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Strong understanding of software architecture principles and design patterns.
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Experience building containerized applications using Docker and Kubernetes technologies.
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Familiarity with front-end application development and modern application frameworks.
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Experience with: CI/CD pipelines, Infrastructure-as-Code, Test automation, Monitoring and observability, Production support processes, Root cause analysis and Performance optimization
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BS or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical discipline.

Additional Requirements:
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Strong written and verbal communication skills.
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Ability to work directly with technical and business stakeholders.
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Experience supporting global onshore/offshore delivery models.
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Strong problem-solving and analytical skills.
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Ability to balance hands-on development responsibilities with technical leadership responsibilities.
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Passion for emerging Analytics, AI, and GenAI technologies.