Generative AI Engineer

• Demonstrated experience shipping production-grade LLM or generative AI systems - prompt and workflow design tradeoffs, model selection and routing decisions, tool use and agent orchestration boundaries, and the distinction between AI guardrails and deterministic application logic
• Experience building automated evaluation pipelines for LLM outputs, including gold set construction, model-based evaluation approaches, prompt regression testing, retrieval quality validation, and failure mode analysis across the full LLM application stack
• Experience implementing human-in-the-loop controls, content guardrails, and schema-based output validation for enterprise AI deployments
• Strong track record designing, building, and operating complex distributed systems in enterprise production environments, with clear ownership of reliability, performance, and operational outcomes
• Experience with CI/CD pipeline design and operation for AI services - including deployment strategies, versioning, and release management in production environments
• Proven ability to define and enforce GenAI engineering standards, patterns, and best practices across a cross-functional team
• Experience designing and operating cloud-native APIs, microservices, and event-driven architectures on Azure or equivalent cloud platform
• Experience integrating AI systems with enterprise data sources, internal APIs, and security controls in compliance-sensitive environments
• Demonstrated track record of shipping production AI systems iteratively - with regular release cadence, feedback incorporation, and continuous improvement
• Bachelor's degree in Computer Science, Engineering, Data Science, or related field, or equivalent practical experience

• Experience designing and operating agentic AI systems and multi-step RAG architectures in production - retrieval quality optimization, chunking strategies, grounding, and ranking tradeoffs
• Hands-on experience with Azure OpenAI, AI Foundry, App Service, Functions, Service Bus, Blob Storage, Key Vault, and Application Insights; familiarity with Bicep for IaC
• Experience with Python frameworks commonly used in production AI services, including FastAPI, asyncio, and Pydantic
• Familiarity with PySpark notebooks for data pipeline development
• Experience deploying and managing containerized AI workloads using Docker or similar technologies
• Familiarity with responsible AI principles, AI governance frameworks, and regulatory considerations relevant to enterprise AI systems
• Familiarity with Bronze/Silver/Gold medallion architecture and staged data quality patterns for enterprise data pipelines
• Domain experience in product data, PIM, ERP, master data management, data governance, ecommerce, or analytics platforms
• Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field

• Prolonged periods in a stationary position at a desk and working on a computer.
• Must be able to communicate effectively via video conferencing, phone, and written correspondence.
• Occasional travel may be required depending on project or business needs.

The work environment is typically in a remote office setting during normal or extended business hours.

Candidates for the position should be able to perform essential job duties in described work environment with or without accommodation.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Infinite Electronics is committed to building a diverse workforce and providing equal employment opportunities to all qualified candidates.

All hiring decisions are based on qualifications, skills, and business needs, without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, age, national origin, disability, or any other status protected by applicable law.