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Job Description
Structured overview of role & requirementsAbout This Role
Own end-to-end design, build, deployment, and operation of reliable data pipelines and AI/GenAI solutions focused on production reliability, trusted data access, and prompt effectiveness in a regulated environment.
Develop and maintain AI agents and LLM-powered capabilities ensuring stable, compliant production operation with observability, trust controls, and escalation paths.
Partner with business, product, governance, and engineering teams to translate ambiguous needs into scalable, maintainable solutions while mentoring colleagues and influencing engineering direction.
Minimum Requirements
Bachelor's degree in computer science, engineering, data science, or related field, or equivalent practical experience.
Typically 7+ years of relevant hands-on experience developing and operating production data, software, AI, or cloud solutions consistent with senior individual contributor role.
Strong Python and SQL skills and experience with Microsoft Azure services including Databricks, Azure Data Factory, Web Apps, Key Vault; plus modern data engineering and AI framework experience (e.g. LangChain, FastAPI).
Work Experience Required: Typically 7+ years relevant experience. Notice period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in independently managing complex components of data and AI landscapes with minimal oversight and strong technical judgment in regulated environments.
Skilled in AI agent and GenAI engineering with practical use of AI-assisted engineering tools, able to balance delivery speed with maintainability, compliance, and quality assurance.
Capable of strategic stakeholder engagement and mentorship, able to translate ambiguous business requirements into governed, scalable solutions and evolve team capabilities.