Summary

We are seeking a highly motivated and analytical Data Scientist II- Agentic AI to join our team. The ideal candidate will have a strong foundation in data science principles, experience working with LLMs, and a passion for developing impactful AI solutions. The team focuses on solutions that improve technical troubleshooting /support for technicians and customers. This role offers the opportunity to work on innovative, high-impact data products within a collaborative team environment. You will contribute to the architecture, development, and deployment of cutting-edge AI-powered applications, collaborating within our expert team and gaining practical experience from senior mentorship.

Key Responsibilities

• Design and implement single and multi-agent systems that can reason, plan, and act to solve complex user problems.
• Define agent behavior, memory, and tool-use strategies with a strong emphasis on correctness, controllability, and user experience.
• Implement AI protocols and frameworks such as ADK/Langchain for A2A orchestration 
• Integrate agents with internal/external systems (knowledge bases, ticketing, diagnostics) via APIs, MCP, and tool orchestration.
• Design persistent memory and state management for multi-turn dialogue
• Build guardrails, safety logic, and human-in-the-loop escalation paths — critical for a support domain where agents' advising is required.
• Develop frameworks for evaluation and observability (LLM as a judge, test cases, agent evaluations, tracking agent quality over time)
• Optimize system performance by analyzing model behavior and failure modes, turning qualitative issues into measurable signals for improvement.

Critical Qualifications

• Bachelor's degree in computer science, Data Science, Engineering, Applied Math, or related fields. Relevant experience may be considered in lieu of a degree.
• 3+ years of relevant work experience in data science and/or machine learning.
• Advanced proficiency in SQL and Python. 
• Ability to write clean, efficient, and reusable code. 
• Agentic or RAG systems experience: You've built at least one system involving tool use, retrieval-augmented generation, multi-step reasoning, or autonomous agents — not just single-shot completions.
• Hands-on LLM experience: You've worked directly with LLM APIs (OpenAI, Gemini, Anthropic, etc.) and understand the practical realities — prompt design, context management, latency, cost, and failure modes.
• Agile Mindset & Collaboration: Proven experience delivering literately, collaborating in a team environment, communicating clearly.

Preferred Qualifications

• Master’s degree in a discipline such as Computer Science, Data Science, Engineering, Applied Math, or related field. 
• Certification in cloud-based data platforms and services (e.g., GCP). 
• Familiarity with agent frameworks (LangGraph, CrewAI, ADK, etc).
• Experience in a Cloud environment (GCP is preferred, but cloud skills are transferable) and building agentic workflows.
• Exposure to modern DevOps and ML Ops practices, including CI/CD, containerization, and orchestration.
• Domain experience in tech support or knowledge management systems.