Senior AI Engineer Job at Abotts (Eden Prairie)

Job Description

Shutterfly is seeking a Senior AI Engineer (Contractor) to accelerate the design, development, and deployment of enterprise AI capabilities across our business. This individual will partner closely with Enterprise Information Services, product teams, and business stakeholders to architect and ship production-grade generative and agentic AI solutions on a multi-cloud, multi-model stack. The ideal candidate is platform-agnostic, deeply hands-on, and comfortable taking ambiguous business problems from whiteboard to production.

Job Responsibility

Design, build, and deploy enterprise-grade AI agents, copilots, and automation workflows that integrate with Microsoft 365, internal systems, and customer-facing applications
Microsoft Copilot Studio: Develop and operationalize agents and low-code/pro-code solutions — custom topics, plugins, knowledge sources, and connectors
Azure AI Foundry: Architect and implement model orchestration, retrieval-augmented generation (RAG), evaluation, and guardrails using model catalog, prompt flow, agent service, and content safety
Anthropic Claude: Integrate Claude models (Opus, Sonnet, Haiku) via the Anthropic API and Bedrock — including prompt caching, tool use, extended thinking, and agentic patterns
Google Cloud Platform: Build and operate AI services using Vertex AI, Gemini, Agent Builder, BigQuery, and associated MLOps tooling
Lead end-to-end model lifecycle: data preparation, fine-tuning/adaptation, evaluation, deployment, observability, and continuous improvement
Establish and enforce responsible AI practices — security, privacy, content safety, bias mitigation, prompt injection defense, and auditability — in alignment with Shutterfly enterprise standards
Partner with Systems Engineering, Security, and Data teams to integrate AI workloads with identity (Entra ID), data platforms, and CI/CD pipelines
Mentor internal engineers and developers
produce reusable patterns, reference architectures, and documentation that elevate the team's AI maturity
Evaluate emerging frameworks, foundation models, and agent platforms
recommend strategic direction

Requirements

8+ years of professional software / ML engineering experience, with 2+ years building production generative AI or agentic systems
Expert-level proficiency in Microsoft Copilot Studio — agent design, topics, custom connectors, Power Platform integration, governance, and lifecycle management
Hands-on expertise with Azure AI Foundry (formerly Azure AI Studio) — model deployment, prompt flow, agent service, evaluations, and content safety
Production experience with Anthropic Claude — Anthropic SDK, prompt caching, tool use, MCP (Model Context Protocol), and multi-turn agent design
Strong working knowledge of Google Cloud Platform — Vertex AI, Gemini, Agent Builder, BigQuery, Cloud Run, and IAM
Proficiency in Python and at least one of TypeScript/Node.js or C#/.NET
Solid grounding in RAG architectures, vector databases (Azure AI Search, Pinecone, Vertex Vector Search), embeddings, and semantic retrieval
Experience with LLM evaluation frameworks, observability (LangSmith, Azure AI Foundry evaluations, custom telemetry), and A/B testing of AI systems
Experience integrating AI with Microsoft 365 (Graph API, Teams, SharePoint, Outlook) and enterprise identity (Entra ID / OAuth2)
Strong understanding of responsible AI, data privacy (GDPR, CCPA), and enterprise security practices
Excellent written and verbal communication
ability to translate technical concepts for non-technical stakeholders

Nice to have

Experience with OpenAI (Azure OpenAI, GPT-4o, o-series), AWS Bedrock, and open-weight models (Llama, Mistral)
Familiarity with agent frameworks (LangGraph, AutoGen, Semantic Kernel, CrewAI, Claude Agent SDK)
Experience with MLOps / LLMOps tooling — MLflow, Kubeflow, Weights & Biases, Vertex AI Pipelines
Background in e-commerce, retail, or consumer-facing applications
understanding of personalization, content generation, and creative workflows
Contributions to open source AI projects or published technical writing
Relevant certifications: Microsoft AI Engineer Associate, Google Professional ML Engineer, AWS ML Specialty
Bachelor’s or Master’s in Computer Science, ML, or related field (or equivalent experience)

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