Staff AI Data Engineer

Staff AI Data Engineer

ADI - Analog Devices

Limerick, Ireland

Overview

As a Staff AI Data Engineer, you will provide technical leadership and hands-on delivery for ADI’s next generation of data and AI solutions. You operate from first principles - reasoning from the fundamentals of distributed systems, data modeling, and machine learning rather than from tooling alone - to design, build, and deploy end-to-end solutions that are highly scalable, performant, secure, and resilient. You are equally strong in advanced data engineering and in applied AI: you can architect a petabyte-scale lakehouse and, in the same breath, design and ship a production AI/GenAI solution on top of it. You plan, design, implement, deploy, and operate; you guide and mentor engineers; and you translate ambiguous business problems into data-driven outcomes with senior stakeholders. You bring strategic, long-term focus on code quality, reliability, reusability, maintainability, DataOps, and MLOps/LLMOps.

Responsibilities

• Architect and deliver end-to-end data and AI solutions - from ingestion and curation to modeling, serving, and consumption - that are scalable, secure, and production-grade.
• Design and build modern data platforms on the lakehouse and cloud data warehouse: streaming and batch ingestion, medallion (Bronze/Silver/Gold) architectures, data mesh patterns, data modeling, data quality, lineage, security, and governance.
• Design, implement, and deploy AI/GenAI solutions on enterprise data - including retrieval-augmented generation (RAG), LLM-powered agents and agentic workflows, vector search, and classical/statistical ML (e.g., anomaly and excursion detection) - and take them through their full lifecycle from prototype to production.
• Build and champion AI-assisted engineering and agentic DataOps - designing LLM-agent orchestration and automation that accelerate data pipeline development, code review, testing, deployment, and operations across the team.
• Stand up MLOps/LLMOps foundations: experiment tracking, model/prompt evaluation, model serving, monitoring, evaluation harnesses, cost and quality guardrails for AI workloads.
• Lead the execution of large-scale, complex data and analytics efforts; scope key business challenges, identify the right data, and provide direction to data analysts, data scientists, data engineers, product managers, and business stakeholders.
• Partner with data platform, infrastructure, and enterprise architecture teams to architect and connect high-quality, resilient data feeds across the enterprise, and ensure architectural alignment.
• Drive innovation by creating new frameworks, standards, reference architectures, prototypes, and automation - including AI-assisted engineering and DataOps tooling.
• Advise and influence business leaders and senior stakeholders with data-driven insights; communicate both the high-level concept and detailed user stories, and build consensus to adopt data- and AI-driven improvements.
• Design, build, and maintain robust processing frameworks for petabyte-scale structured, semi-structured, and unstructured data to enable actionable insights and analytics.
• Build dashboards and data products using enterprise BI tools such as Power BI (preferred) and Tableau.

Qualifications

• 10+ years of experience in software/data engineering, including 5+ years in data engineering and demonstrable experience designing and shipping AI/ML or GenAI solutions to production.
• Degree in Computer Science, Electrical Engineering, Computer Engineering, Data Science, or a related field (advanced degree a plus).
• First-principles command of distributed systems, streaming systems, and data engineering fundamentals (Spark, Kafka, Delta Lake, orchestration).
• Deep knowledge of Python, SQL, database and data-model design, and master-data strategies.
• Proven ability to design, architect, and roll out data products and AI solutions, owning them through their entire lifecycle.
• Hands-on experience building applied AI on enterprise data - RAG, LLM agents, vector search, or production ML - with a working understanding of evaluation, guardrails, and cost/quality trade-offs.
• Experience mentoring and leading technical staff and incorporating modern software development tools and practices.
• A confident peer influencer with strong communication skills who quickly establishes credibility and can lead cross-functional technical teams and engage business stakeholders.

Additional Qualifications (Preferred)

• Industry background in a semiconductor manufacturing company - experience with semiconductor design & manufacturing data supporting vertical business units.
• Experience operating in a data-mesh/enterprise data-platform environment across many source systems (ERP, CRM, engineering/IP telemetry).
• Experience metering, evaluating, or governing AI/GenAI workloads (usage, cost, and quality).
• Certifications in cloud platforms, Databricks, Snowflake, or data/AI engineering.