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# Data Scientist II

- **Company:** Robert Half
- **Location:** San Ramon, CA, United States
- **Experience:** Expert
- **Salary:** $119,000.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, A/B Testing, Artificial Intelligence, Monitoring of Systems, Python (Programming Language), Machine Learning, Chatbots, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Information Technology, Automation Anywhere
- **Published:** October 26, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3467079607&tx=KR1111FFK&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or related fields.
 * 5+ years of experience in applied ML, AI development, or advanced data science roles.
 * Hands-on experience building and deploying LLM-based agents, RAG pipelines, and multimodal Gen AI systems.
 * Proficiency in Python and Gen AI frameworks
 * Strong understanding of agent orchestration frameworks (LangGraph, LangChain, AutoGPT, or equivalent).
 * Demonstrated expertise in benchmarking, A/B testing, and model monitoring for AI systems.
 * Experience developing and maintaining prompt engineering standards and frameworks.
 * Ability to evaluate and optimize model performance across different LLMs and architectures.
 * Strong communication and collaboration skills across product, engineering, and business teams.
 * Proven track record of mentoring team members and driving innovation in AI workflows.
 * Familiarity with internal experimentation, observability, or AI governance tools is a plus.
 * Contributions to open-source projects, research publications, or AI community initiatives is a plus.

## Description

* Design and implement Gen AI-powered agents that solve real business challenges and streamline internal workflows.
 * Extend and optimize the internal agent evaluation framework to ensure reliable, high-performing, and explainable agents.
 * Build benchmarking and monitoring systems to assess orchestration strategies and model performance in production.
 * Conduct experiments to evaluate the impact of model or architecture changes, balancing performance, cost, and scalability.
 * Build on existing prompt engineering frameworks to standardize best practices and eliminate "prompt debt."
 * Move beyond chatbots to create ambient, context-aware agents that boost efficiency and unlock new productivity avenues.
 * Collaborate with engineering teams to advance the internal agentic platform, focusing on orchestration, observability, and optimization.
 * Mentor and guide junior data scientists and software engineers on Gen AI techniques and frameworks.
 * Partner with product managers to assess technical feasibility, estimate level of effort (LoE), and prioritize development initiatives.
 * Bring innovative ideas to evolve agentic architecture and continuously advance internal AI capabilities.
 * Communicate complex AI concepts effectively to non-technical stakeholders, supporting organizational learning and adoption.
 * Lead roadshows and demos to advocate for Gen AI tools and drive cultural change across the enterprise.