Senior Data Scientist - AI Engineering

Role Overview

We seek an experienced Senior Data Scientist specializing in AI Engineering to architect, construct, and deploy advanced agentic AI systems tailored for marketing analytics applications. This hands-on position emphasizes building production-ready language model agents, tools, and data pipelines rather than research or strategic architecture.

Key Responsibilities

• Engineer agentic AI systems that coordinate multi-step tool-using agents automating marketing workflows including segmentation narratives, campaign insights, reporting, and data quality assurance.
• Create and deploy Claude Skills, custom function-calling workflows, and tools to enhance agent capabilities with controlled guardrails.
• Develop and sustain Retrieval-Augmented Generation pipelines focusing on chunking, embedding, vector store structuring, retrieval optimization, and grounding using internal marketing and media datasets.
• Implement automated evaluation frameworks such as LLM-as-judge for large-scale accuracy, hallucination, and consistency assessment of agent/model outputs.
• Lead LLMOps and AIOps activities, including prompt versioning, model rollout strategies, latency and cost monitoring, drift detection, and automated regression checks for language model pipelines.
• Apply MLOps principles by setting up CI/CD pipelines for machine learning workflows, containerization (Docker/Kubernetes), experiment tracking (MLflow, Weights & Biases), and reproducible deployments on AWS, GCP, and Azure cloud platforms.
• Integrate APIs from Anthropic Claude and OpenAI into production pipelines featuring structured output management, function/tool invocation, and multi-agent orchestration.
• Build validation harnesses and safety guardrails involving output verification, fallback mechanisms, and human-in-the-loop checkpoints.
• Write production-grade Python and SQL code supporting data extraction, pipeline development, and agent tooling.
• Collaborate with fellow data scientists to embed agentic and language model components into existing marketing mix and targeting workflows.
• Produce clear documentation covering architecture designs, prompt engineering decisions, and evaluation methods to ensure reproducibility and team collaboration.
• Stay abreast of ongoing developments in agentic AI to incorporate emerging tools, frameworks, and techniques beneficial to the team.

Qualifications and Skills

• Minimum 4 years of professional AI/ML experience, including at least 2 years dedicated to generative AI implementations.
• Proven expertise in applied machine learning, data science, and agentic AI engineering with client-facing delivery experience.
• In-depth knowledge of evaluation processes, metrics, and dataset creation for language model systems.
• Demonstrated ability in model selection and advanced prompt engineering, including structured outputs and tool-using prompts.
• Proficient in Python and mainstream machine learning frameworks such as PyTorch, TensorFlow, and Scikit-learn.
• Strong practical experience with LLM fine-tuning, retrieval-augmented generation design, Claude Code, OpenAI Codex, and agentic workflows.
• Expertise in RAG architecture choices like chunking, embedding strategies, retrieval tuning, and reranking, with evaluation proficiency.
• Experience implementing full agentic AI software development lifecycle (SDLC).
• Hands-on use of GenAI services on Azure, AWS, or Snowflake platforms leveraging native AI tools (Azure OpenAI, AWS Bedrock, Snowflake Cortex) for building intelligent, governed data solutions.
• Familiarity with vibe coding environments such as AntiGravity, Cursor, and Visual Studio Code is highly preferred.
• Track record of delivering end-to-end generative AI MVPs in Python—including RAG agent builds and evaluation frameworks—prepared for production deployment.
• Excellent communication abilities and a strategic, stakeholder-focused mindset.

Additional Information

• Competitive Compensation: Your expertise is rewarded with a salary reflecting your knowledge and contributions.
• Rapid Advancement: Enjoy a dynamic workplace fostering fast career growth through mentorship, tools, and new challenges.
• Innovation Labs: Participate in "Idea Tanks" to propose, test, and collaborate on transformative concepts.
• Learning Opportunities: Engage in informal "Growth Chats" to develop skills alongside experienced peers.
• Refreshment Zone: Access to snacks to maintain energy and inspiration throughout workdays.
• Recognition Programs: Receive frequent acknowledgments, including Hive-Fives and public shoutouts rewarding excellence.
• Certification Support: Company-sponsored certifications in AI, Data Science, Cloud, and Analytics to boost your expertise.

Eligibility

Applicants with any graduate-level education are invited to apply.