Data Engineer III, AI Platform
About The Position
The Data Engineer III, AI Platform builds and operates reusable data pipelines and AI-ready platform services for Hawaii Mobility. Reporting to the Manager, Data Engineering, within the Data Visualization, Analytics & Automation function, this senior individual contributor builds, tests, releases, and observes production workloads on Databricks and Azure. The role engineers governed feature, context, and evaluation pipelines for predictive and generative AI, implements data and platform components of MLOps and LLMOps patterns designed with the Data & AI Architect, owns reliability for shipped assets, and mentors engineers through review and pairing. The role develops reusable ingestion, transformation, orchestration, and serving patterns for batch and streaming workloads, along with connectors, recovery paths, schema evolution, and certified datasets. It engineers AI feature, retrieval, context, evaluation, monitoring, and feedback pipelines; maintains the semantic and ontology layer informing Servco's LLMs and extending data understanding to platforms such as OpenAI and Claude; and helps tune Servco's LLMs and implement enterprise AI agents. The position also implements reproducible environments, infrastructure as code, CI/CD, observability, and runbooks; tunes performance and cloud costs within approved architecture and security standards; and owns reliability, incident response, and recovery for delivered assets. It partners with data engineering, analytics, architecture, and operations teams, mentors newer engineers, documents reusable practices, and trains forward deployed team members in implementing AI solutions to established standards.
Requirements
- Relevant degree or equivalent demonstrated experience.
- 6–10 years building production data pipelines and platforms.
- Strong Python, SQL, Spark, and Databricks engineering experience on Azure or a comparable cloud.
- Experience building reusable frameworks, automated tests, CI/CD, infrastructure as code, and observable production services.
- Hands-on experience with AI-ready pipelines for features, retrieval corpora, or evaluation data, and practical MLOps or LLMOps deployment and monitoring.
- A record of operating reliable data products, resolving incidents, tuning cost and performance, and mentoring engineers.
- Curiosity about unfamiliar systems and ability to anticipate how changes in business workflows affect data and platform design.
Nice To Haves
- Experience with MLflow or comparable model lifecycle tools, Unity Catalog, vector search, event integration, and automotive or retail operations data.
Responsibilities
- Build and own reusable ingestion, transformation, orchestration, and serving patterns for batch and streaming workloads on Databricks.
- Develop connectors, recovery paths, schema evolution, and certified datasets for reporting, applications, and AI.
- Implement automated reconciliation, data quality, freshness, lineage, and access controls for production pipelines and AI context.
- Engineer feature, context, and retrieval pipelines, including document ingestion, metadata, embeddings, and indexes, according to solution designs agreed with the Data & AI Architect.
- Build versioned evaluation data, model and agent monitoring feeds, feedback capture, and identity-aware feature tables, APIs, and event streams.
- Implement data and platform components of MLOps and LLMOps delivery.
- Maintain and develop the semantic and ontology layer that informs Servco's LLMs and extends data understanding to platforms such as OpenAI and Claude.
- Tune Servco's LLMs for accuracy and review feedback through the Genie admin console.
- Assist with implementing and maintaining AI agents within enterprise platforms to automate repetitive work and reduce bottlenecks in solution development.
- Implement reproducible environments, infrastructure as code, CI/CD, logging, monitoring, alerting, and runbooks.
- Tune workload performance and cloud costs within approved architecture and security standards.
- Own reliability, incident response, and recovery for shipped assets; improve testing and release practices based on production learning.
- Partner with the Manager, Data Engineering, Analytics Engineers, architecture, and operators to translate customer and operating needs into dependable data products and support agreed shared capabilities.
- Mentor newer engineers through code review and pairing, document reusable patterns, and retain critical know-how in Servco-controlled systems.
- Train and support forward deployed team members implementing AI solutions in line with architecture, implementation, and platform standards.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
