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Job Description
Structured overview of role & requirementsAbout This Role
Own and operate end-to-end data pipelines, datasets, and AI agents including design, deployment, reliability, observability, and governance for analytics, ML, and GenAI use cases.
Build and maintain AI-enabled business workflows with accountability for prompt effectiveness, escalation controls, and compliance in a regulated environment.
Partner cross-functionally to translate ambiguous needs into scalable, maintainable solutions, mentor colleagues, and influence technical direction with limited oversight.
Minimum Requirements
Bachelor's degree in computer science, engineering, data science, or related field, or equivalent experience.
Typically 4+ years of relevant hands-on experience building and operating production data, software, AI, or cloud solutions.
Strong Python and SQL skills; experience with Microsoft Azure services including Databricks, Azure Data Factory, and related cloud deployment tools.
Experience with modern data engineering, AI frameworks (e.g., LangChain), containerization (Docker, Kubernetes), and source control (GitHub).
Ideal Candidate Profile
Technical operator comfortable owning complex components end-to-end in data engineering and AI agent development with strong reliability, quality, and compliance focus.
Experienced in using AI-assisted engineering tools effectively, with strong judgement around generated outputs and risk implications.
Able to engage diverse stakeholders and mentor peers, translating business goals into practical, scalable technical solutions in regulated, cross-functional settings.