Senior Analyst, AI Engineer
Role details
Job location
Tech stack
Job description
As an AI Engineer, you will play a key role in building, testing, and deploying cutting-edge artificial intelligence solutions natively on Google Cloud Platform (GCP). Working closely with senior engineers, you will leverage Vertex AI to integrate Large Language Models (LLMs), build Retrieval-Augmented Generation (RAG) pipelines, and develop Agentic AI systems (equipping Gemini models with tools, API access, and reasoning loops). This role is ideal for an early-career engineer who has strong Python skills, a solid grasp of foundational cloud principles, and a passion for building next-generation action-oriented AI., * GCP AI Development: Help build and configure GenAI applications utilizing the Vertex AI SDK and the Gemini model family.
- Agentic Workflows: Assist in building AI agents. This includes setting up Vertex AI Extension calls, defining function schemas for Gemini tool-use, and managing agent memory/reasoning loops.
- Data & Vector Pipelines: Support the ingestion of unstructured enterprise data into Vertex AI Vector Search or BigQuery to power RAG and grounding mechanisms.
- Prompt Engineering & Evaluation: Design, test, and iterate on system instructions. Use Vertex AI's evaluation tools to check for response accuracy, safety, and hallucinations.
- Cloud Integration: Assist in deploying and hosting lightweight AI APIs, agent endpoints, or microservices using Cloud Run or Cloud Functions.
- Observability & Debugging: Monitor and debug agent execution paths and API latency using Google Cloud Logging and Cloud Trace.
- Continuous Learning: Actively research and stay up-to-date with the rapidly evolving GenAI landscape, bringing fresh ideas, open-source frameworks, and tools to the team.
Requirements
- Programming Languages: Strong proficiency in Python and standard SQL.
- GCP Infrastructure (Basic familiarity): Experience or projects utilizing Google Cloud Platform (e.g., Cloud Storage, Cloud Run, BigQuery).
- Vertex AI Suite: Basic exposure to Vertex AI Studio, Model Garden, Gemini APIs, or Vertex AI Vector Search.
- GenAI / Agentic Frameworks: Conceptual understanding of LLM prompt engineering, embeddings, and agentic workflows (experience with Python frameworks like LangChain, LangGraph, LlamaIndex, or Vertex AI Agent Builder is highly regarded).
- Developer Fundamentals: Comfort with Git, VS Code/Jupyter, and writing clean, modular Python code., * Bachelor's degree in mathematics, Statistics, Engineering, Computer Science, other related field, or equivalent years of relevant work experience is preferred.
- 1+ years of experience preffered
- Knowledge of clinical domain and datasets is a major plus
- Experience in Generative AI, RAG implementation, re-ranking, vector db, embeddings etc. is a plus
- Knowledge of Machine Learning and related technologies such as Tensorflow Python, Torch, Amazon SageMaker, Jupiter Notebooks, git.
- Understanding of cloud data engineering and integration concepts.
- Strong mathematical and statistical skills.
- Prior experience in Healthcare industry and knowledge of clinical data.
- Experience with Google Cloud Platform.
- Knowledge of software solutions such as data warehouses and integration platforms.
- Knowledge of Agile development skills and experience., Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply.
Benefits & conditions
Anticipated salary range: $80,500 - $103,410
Bonus eligible: No
Benefits: Cardinal Health offers a wide variety of benefits and programs to support health and well-being.
- Medical, dental and vision coverage
- Paid time off plan
- Health savings account (HSA)
- 401k savings plan
- Access to wages before pay day with myFlexPay
- Flexible spending accounts (FSAs)
- Short- and long-term disability coverage
- Work-Life resources
- Paid parental leave
- Healthy lifestyle programs