Sr Data Scientist @ Employer

Company Summary

As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com

Position Responsibilities

About the Role

We are seeking a motivated AI Data Scientist to join Deltek’s growing AI Center of Excellence team to design, build, evaluate, and optimize enterprise AI solutions leveraging Large Language Models (LLMs), AI Agents, Retrieval-Augmented Generation (RAG), multimodal AI, open-source AI models, and emerging foundation model technologies.

This role is focused exclusively on AI innovation and implementation rather than traditional analytics or reporting. The ideal candidate will develop intelligent AI systems, evaluate model performance, build agentic workflows, and contribute to the adoption of AI-powered business solutions, working with guidance from senior team members on larger or more complex initiatives.

The successful candidate combines solid expertise in Generative AI, machine learning, prompt engineering, and AI evaluation with a passion for translating cutting-edge AI capabilities into scalable business outcomes. This role reports to the Senior Director, AI Solutions.

Key Responsibilities

Generative AI Solution Development

• Design, develop, and deploy Generative AI solutions for defined use cases, following established architecture patterns.
• Build AI applications leveraging Large Language Models (LLMs) and SLMs.
• Develop Retrieval-Augmented Generation (RAG) pipelines, including chunking, embedding, retrieval, and re-ranking.
• Implement conversational AI, AI copilots, and intelligent assistants.
• Design and refine prompt engineering strategies.
• Contribute to multimodal AI solutions involving text, image, audio, and document understanding.

Agentic AI & Autonomous Systems

• Develop AI Agents capable of reasoning and task execution for well-defined business workflows.
• Build components of multi-agent frameworks and agent orchestration solutions.
• Develop automated workflows integrating enterprise systems and business processes.
• Implement tool-calling, function-calling, and agent memory patterns.
• Tune agent planning, reasoning, and decision-making behavior based on test results and feedback.

AI Model Evaluation & Optimization

• Apply and extend evaluation frameworks for AI solutions.
• Build benchmarks and test sets for quality, accuracy, groundedness, hallucination detection, and safety.
• Evaluate and compare foundation models for business use cases and share findings with the team.
• Improve AI system performance through prompt tuning, fine-tuning, and model optimization.
• Monitor AI solution effectiveness and recommend enhancements.

AI Engineering & Deployment

• Collaborate with engineering teams to deploy AI solutions into production environments.
• Build AI pipelines and support inference architectures.
• Support integration of AI services with enterprise applications and workflows.
• Partner with platform teams to improve AI cost, latency, scalability, and performance.
• Implement AI observability, monitoring, and governance controls as defined by the team.

Responsible AI & Governance

• Apply Responsible AI principles throughout the AI lifecycle.
• Evaluate solutions for bias, fairness, explainability, security, and compliance.
• Support AI governance policies, risk assessments, and model validation processes.
• Implement safeguards and guardrails for enterprise AI applications.

AI Innovation & Research

• Stay current with advancements in Generative AI, foundation models, open-source AI, and agentic systems.
• Evaluate emerging AI technologies and share recommendations with the team.
• Create proof-of-concepts and pilot solutions using next-generation AI capabilities.
• Contribute to enterprise AI strategy and AI capability development.

Qualifications

Required Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or related field.
• 3+ years of experience developing AI/ML solutions.
• 1+ year of hands-on experience with Agentic AI, Generative AI, and Large Language Models.
• Experience building AI copilots, AI assistants, RAG solutions, or AI Agents.
• Proficiency in Python and modern AI frameworks.
• Experience supporting the integration of AI solutions into enterprise environments.
• Strong communication and stakeholder engagement skills.

Preferred Qualifications

• Master's degree in AI, Computer Science, Machine Learning, or related discipline.
• Exposure to Microsoft Azure AI Foundry, Azure OpenAI, OpenAI APIs, Anthropic Claude, Gemini, or similar platforms.
• Familiarity with fine-tuning, model adaptation, embeddings, and vector databases.
• Working knowledge of Agentic AI frameworks such as Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, A2A, MCP or similar technologies.
• Exposure to deploying AI solutions in regulated enterprise environments.
• AI-related certifications from Microsoft, OpenAI, AWS, or Google Cloud.

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