Associate AI Engineer

Associate AI Engineer

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 Pogue's AI production team, this individual develops, tests and supports AI and automation capabilities built on Pogue's 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 Pogue's 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.

0–3 years' professional experience in software development, data engineering or a related technical role.

Bachelor's degree in computer science, software engineering, information systems, data science or a related field, or commensurate experience.

Primary Responsibilities:

• 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 Pogue's 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 Pogue's 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 Protégé, OWL, RDF or SPARQL
• Metadata, data lineage, document management or construction & project-control systems
• TypeScript, C# or another modern language
• CI/CD, containerized services, monitoring, cost management or secure enterprise integration