Associate AI Engineer

Job Description

POSITION SUMMARY The Associate AI Engineer is an early career builder responsible for moving approved ideas from a governed backlog into reliable well documented solutions Working as part of Pogues AI production team this individual develops tests and supports AI and automation capabilities built on Pogues Microsoft Fabric data platform and contributes to the enterprise ontology and knowledge foundation that those solutions depend on This is a hands on development role with structured mentorship Design review and pairing with Pogues Principal Solutions Architect are a standing part of the work and this individual is expected to partner directly with business owners so that what gets built is actually used EXPERIENCE \& EDUCATION 03 years professional experience in software development data engineering or a related technical role Bachelors degree in computer science software engineering information systems data science or a related field or commensurate experience PRIMARY RESPONSIBILITIES AI Solution Development Develop test \& improve bounded AI and automation capabilities using VS Code SQL APIs Git \& Pogue approved cloud services Support solutions such as permission aware enterprise search retrieval augmented generation RAG internal assistants workflow support \& AI enabled analytics Translate approved backlog items into requirements technical tasks acceptance criteria \& small releases that can be measured \& safely supported Create prototypes when discovery is needed then help convert validated prototypes into maintainable services \& reusable patterns Participate in design review with the Principal Solutions Architect before development begins \& carry approved designs through to release Data \& Enterprise Knowledge Work with Microsoft Fabric lakehouse data governed Gold business objects semantic models metadata \& shared business definitions Help connect structured data \& approved documents through secure APIs \& retrieval patterns while preserving source permissions citations versions \& effective dates Contribute to Pogues enterprise ontology \& knowledge foundation by documenting objects relationships definitions ownership \& authoritative sources Build only on data confirmed as validated in the Gold layer Quality Security \& Trust Document architecture assumptions decisions data flows interfaces tests deployment steps \& operating runbooks so another team member can understand \& support the solution Evaluate accuracy failure modes access behavior latency cost \& usefulness; turn results into clear release recommendations Follow Pogues identity role based access data classification approved model logging monitoring \& human approval requirements Surface uncertainty security concerns \& data quality issues early; propose practical options instead of hiding risk Business Partnership \& Adoption Work directly with business owners \& subject matter experts to understand the decision or workflow before selecting a technical approach Explain tradeoffs in plain language ask focused questions demonstrate progress \& incorporate feedback from technical \& nontechnical teammates Support adoption with concise guides examples training materials \& responsive follow through after launch Support the AI Champions Network as solutions roll out to project teams REQUIRED SKILLS Team Player Teachable Curious \& self directed Able to write \& troubleshoot code in VS Code Working knowledge of SQL Working understanding of REST APIs Git based collaboration testing \& basic cloud concepts Secure handling of credentials \& data Able to explain a technical project the decisions personally made the tradeoffs \& how the result was validated Clear written communication Able to relate to \& communicate with a diverse group of professionals Ability to work individually \& as part of a team Self motivated \& driven Highly organized \& detail oriented Highly analytical thinker Positive Attitude Internal \& external customer service Willingness to ask for context when requirements are incomplete Minimum 20 hrs of Continued Education yearly TECHNICAL PROGRAM EXPERIENCE not required Microsoft Azure or Fabric OneLake or lakehouse patterns Power BI Azure AI Search Azure OpenAI or Azure AI Foundry LLM applications RAG embeddings evaluation prompt or model lifecycle management agents or workflow automation Coursework or project work in knowledge representation semantic modeling enterprise ontologies or knowledge graphs including Protg OWL RDF or SPARQL Metadata data lineage document management or construction \& project control systems TypeScript C or another modern language CICD containerized services monitoring cost management or secure enterprise integration