AI Engineer

AI Engineer

W2 Contract-to-Hire

Pay Rate: $65 - $75 per hour

Location: Dublin, CA - Hybrid Role

Job Summary:

We are seeking a highly motivated and experienced AI Engineer to join our Enterprise Architecture and Artificial Intelligence team. This role is responsible for the hands-on design, development, and delivery of intelligent digital assistants, AI agents, and agentic solutions leveraging the Microsoft AI ecosystem, including Azure AI Foundry, Azure services, Copilot Studio, and the Power Platform, alongside pro-code development using Python and other programming languages.

Duties and Responsibilities:

• Develop and Deliver AI Assistants and Agent-Based Solutions


• Design, build, test, and deploy intelligent digital assistants and AI agents using Microsoft Copilot Studio, Azure AI Foundry Agent Service, Azure AI Search, and other Azure services, with hands-on ability to select and implement the appropriate low-code or pro-code agent approach.


• Implement agentic workflows and multi-agent orchestration patterns using both low-code platforms (Copilot Studio, Power Platform) and pro-code approaches (Python, SDKs, APIs).


• Develop and maintain retrieval-augmented generation (RAG) pipelines, including data ingestion, vector indexing, prompt engineering, and grounded responses leveraging enterprise data sources.


• Participate in the Full Software Development Lifecycle (SDLC)


• Contribute to all phases of solution delivery, including requirements analysis, solution design, development, testing, deployment, and post-production support.


• Write clean, well-documented, and maintainable code in accordance with engineering best practices and enterprise standards.


• Support CI/CD pipelines and implement LLMOps practices for effective management of models, prompts, and agent lifecycles.


• Integrate AI Solutions with Enterprise Systems and Platforms


• Develop and consume APIs, connectors, and integration workflows to connect AI solutions with enterprise data sources and business applications, including Azure Cosmos DB, Microsoft Dataverse, SQL databases, file systems, and SaaS platforms.


• Work with enterprise integration platforms (e.g., MuleSoft, Azure API Management, Azure Integration Services) and Microsoft Graph connectors to enable seamless and secure data access.


• Leverage AI gateways, the Model Context Protocol (MCP), and emerging interoperability frameworks to enable secure, governed, and extensible communication between agents and enterprise systems.


• Contribute to Broader AI Initiatives


• Collaborate with third-party partners to design and deploy video analytics and computer vision solutions (e.g., in-store customer experience, safety monitoring, and compliance use cases).


• Support the development and operationalization of additional AI/ML use cases such as demand forecasting, personalization, and intelligent process automation.


• Support AI Governance, Security, and Responsible AI Practices


• Implement responsible AI controls, including guardrails, content filtering, and security measures, in alignment with enterprise architecture and AI Center of Excellence (CoE) guidelines.


• Ensure compliance with data privacy, security standards, and applicable regulatory requirements.


• Contribute to the development and documentation of reusable AI patterns, frameworks, and reference architectures.


• Collaborate and Communicate Across Teams


• Partner with solution architects, data engineers, product managers, and business stakeholders to translate requirements into high-impact AI solutions.


• Provide technical input for estimation, planning, and delivery of project milestones.


• Participate in architecture reviews and contribute to the continuous improvement of AI engineering standards and practices.


• Drive Continuous Learning and AI Innovation


• Stay current with emerging AI tools, frameworks, models, and industry trends, particularly within the retail domain.


• Promote knowledge sharing through technical demos, workshops, and documentation to strengthen AI capabilities across the organization.

Requirements and Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a related technical discipline.


• Minimum of 4 years of experience in software engineering, AI/ML development, or a related technical field.


• Hands-on experience designing, building, and deploying AI/ML or intelligent automation solutions in production or near-production environments.


• Demonstrated experience with Microsoft Azure AI services, including Azure AI Foundry, Azure OpenAI, and Azure AI Search.


• Hands-on experience designing and delivering agents in both Microsoft Copilot Studio and Azure AI Foundry Agent Service, including topics, actions, tools, knowledge grounding, orchestration, testing, deployment, monitoring, and integration with Power Platform services such as Power Automate, Power Apps, and Dataverse.


• Solid understanding of generative AI concepts, including retrieval-augmented generation (RAG), prompt engineering, vector databases, and orchestration patterns.


• Experience developing and integrating APIs and REST services, along with familiarity with enterprise integration platforms such as MuleSoft, Azure API Management, and Microsoft Graph connectors.


• Strong proficiency in Python, with demonstrated experience using generative AI libraries and agent frameworks such as LangGraph, LangChain, and OpenAI/Azure OpenAI SDKs, together with Azure Cosmos DB, Microsoft Dataverse, and vector database integrations to build and integrate LLM-powered and agentic solutions.


• Working knowledge of AI gateways, the Model Context Protocol (MCP), and emerging standards for agent interoperability and tool orchestration.


• Strong understanding of software development lifecycle (SDLC) methodologies, including Agile/Scrum practices.


• Hands-on experience using Visual Studio Code with GitHub Copilot for AI-assisted development, agent development, debugging, testing, code maintenance, and collaboration, together with experience in CI/CD pipelines, Git-based version control, and modern DevOps practices.


• Understanding of AI security, data privacy, responsible AI principles, and regulatory compliance requirements.


• Understanding of AI FinOps principles, including AI service cost drivers and strategies for developing cost-efficient solutions and optimizing usage and spend.


• Strong analytical thinking and problem-solving abilities, with the capacity to navigate ambiguity and complex challenges.


• Excellent communication and collaboration skills, with the ability to effectively engage both technical and non-technical stakeholders.

Preferred Qualifications:

• Microsoft certifications such as Azure AI Engineer Associate, Power Platform Developer Associate, or Azure Developer Associate.


• Experience with computer vision technologies (e.g., Azure AI Vision, Azure AI Video Indexer, OpenCV).


• Familiarity with agentic AI frameworks and multi-agent orchestration tools (e.g., AutoGen).


• Exposure to LLMOps tooling and best practices for managing model, prompt, and agent lifecycles in production environments.

Bayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate.

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