Director Data Scientist (GenAI) and Agentic Engineering

Job Description

Role Overview:As a GenAI and Agentic AI Engineering Hands-on Leader at Blend, you will be responsible for leading delivery, client excellence, and innovation in designing and implementing enterprise-grade AI solutions. Your role will involve a combination of technical leadership and hands-on experience in architecting end-to-end AI/ML systems using cloud-native architecture.Key Responsibilities:- Lead P&L and revenue generation by developing solutions and leading Agentic Initiatives while being hands-on in code development.- Translate business needs into testable GenAI and Agentic Engineering solutions with clear outputs and measurable success criteria.- Run feasibility assessments to choose the right approach for prompting vs RAG vs fine-tuning vs classical ML.- Design prompting strategies, iterate based on evaluation results, and establish prompt iteration methodology.- Define the evaluation plan for GenAI systems and agentic workflows including fairness and bias considerations.- Own experimentation and model improvements by running structured experiments and providing recommendations for improvements.- Deliver an engineering-ready handoff including prompt packages, RAG configuration, tool schemas, datasets, and evaluation metrics.- Design scalable and secure Agentic AI architectures adhering to best practices in data engineering and MLOps.Qualifications:- 15-17 years of overall AI/ML experience with at least 4 years of Generative AI solutions.- Strong background in applied ML, data science, LLM, and Agentic AI Engineering Systems.- Deep expertise in evaluation design, metrics, and dataset curation for LLM systems.- Proficiency in Python and major ML frameworks like PyTorch, TensorFlow, and Scikit-learn.- Experience in LLM fine-tuning, RAG Context Engineering, Claude Code, Open AI Codex, and Agentic Workflows.- Must have implemented Agentic AI SDLC and worked with GenAI on Azure, AWS, or Snowflake.- Proven ability to build end-to-end GenAI MVPs in Python and prepare them for production handoff.- Excellent communication and stakeholder management skills with a strategic mindset.Additional Information:Blend is a premier AI services provider dedicated to co-creating impactful solutions for clients through data science, AI, technology, and people. The company aims to unlock value and foster innovation by harnessing world-class talent and data-driven strategy. Joining Blend means being at the forefront of AI innovation, working with a collaborative team of experts, and contributing to bold visions for the future of AI. Role Overview:As a GenAI and Agentic AI Engineering Hands-on Leader at Blend, you will be responsible for leading delivery, client excellence, and innovation in designing and implementing enterprise-grade AI solutions. Your role will involve a combination of technical leadership and hands-on experience in architecting end-to-end AI/ML systems using cloud-native architecture.Key Responsibilities:- Lead P&L and revenue generation by developing solutions and leading Agentic Initiatives while being hands-on in code development.- Translate business needs into testable GenAI and Agentic Engineering solutions with clear outputs and measurable success criteria.- Run feasibility assessments to choose the right approach for prompting vs RAG vs fine-tuning vs classical ML.- Design prompting strategies, iterate based on evaluation results, and establish prompt iteration methodology.- Define the evaluation plan for GenAI systems and agentic workflows including fairness and bias considerations.- Own experimentation and model improvements by running structured experiments and providing recommendations for improvements.- Deliver an engineering-ready handoff including prompt packages, RAG configuration, tool schemas, datasets, and evaluation metrics.- Design scalable and secure Agentic AI architectures adhering to best practices in data engineering and MLOps.Qualifications:- 15-17 years of overall AI/ML experience with at least 4 years of Generative AI solutions.- Strong background in applied ML, data science, LLM, and Agentic AI Engineering Systems.- Deep expertise in evaluation design, metrics, and dataset curation for LLM systems.- Proficiency in Python and major ML frameworks like PyTorch, TensorFlow, and Scikit-learn.- Experience in LLM fine-tuning, RAG Context Engineering, Claude Code, Open AI Codex, and Agentic Workflows.- Must have implemented Agentic AI SDLC and worked with GenAI on Azure, AWS, or Snowflake.- Proven ability to build end-to-end GenAI MVPs in Python and prepare them for production handoff.- Excellent communication and stakeholder management skills with a strategic mindset.Additional Information:Blend is a premier AI services provider dedicated to co-creating impactful solutions for clients through data science, AI, technology, and people. The company aims to unlock value and foster innovation by harnessing world-class talent and data-driven

Keyskills :
data scienceSnowflakePythonCursorstakeholder managementAI servicesAI technologyLLMAzure AIMachine Learning ecosystemsPyTorchTensorFlowScikitlearnLLM finetuningRAG Context EngineeringClaude CodeOpen AI CodexAgentic Workflowsvibe coding