AI Engineer

This is a fully remote position, open to applicants in California, +12 more states.

📋 Description

• Design, create, implement, and maintain effective AI solutions that address business challenges and provide measurable benefits.

• Collaborate with business leaders, subject matter experts, the AI Enablement Lead, and stakeholders to grasp workflows, user needs, data dependencies, risks, and success criteria.

• Convert business requirements into solution architecture, user stories, delivery plans, and quantifiable outcomes.

• Convey options, limitations, tradeoffs, and recommendations to both business and technical audiences.

• Develop, test, deploy, and sustain AI agents, copilots, workflow automation, integrations, and AI-driven applications.

• Utilize Microsoft Copilot Studio, Azure services, APIs, connectors, Python and/or C#, and other approved technologies for solution development.

• Create integrations with enterprise applications, knowledge bases, and both structured and unstructured data.

• Formulate prompts, agent instructions, grounding strategies, tools, connectors, and reusable components.

• Implement RAG, semantic/vector search, embeddings, agentic patterns, and model orchestration as appropriate.

• Take ownership or significantly contribute to architectural decisions, including the choice between Copilot Studio and custom Azure solutions.

• Employ SDLC practices across all phases including requirements, architecture, development, code review, testing, release management, documentation, support, and retirement.

• Utilize source control, CI/CD, environment separation, configuration management, and repeatable deployment methodologies.

• Conduct unit, integration, functional, regression, security, and user-acceptance testing.

• Develop logging, monitoring, usage analytics, performance metrics, and alerts; diagnose production issues and execute root-cause analysis.

• Produce architecture diagrams, technical specifications, runbooks, support documentation, and user manuals.

• Establish controls for identity and access, data privacy, human oversight, source grounding, output validation, and auditability.

• Analyze and reduce hallucinations, prompt injection, unsafe or inaccurate outputs, bias, data leakage, and inappropriate tool actions.

• Evaluate knowledge and data readiness, collaborating with content owners to enhance quality, permissions, organization, and lifecycle management.

• Partner on pilots, rollouts, user enablement, adoption, feedback collection, and measurement of business outcomes.

• Oversee solution reliability and usage, prioritize engineering improvements, and contribute to the AI delivery backlog and roadmap.

• Uphold and exemplify IMA’s core values while promoting diversity, equity, and inclusion.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Analytics, or a related field, or equivalent practical experience.

• A minimum of three years of experience in software engineering, application development, automation, AI solution delivery, or a related technical area.

• At least one year of hands-on experience in designing and implementing AI agents, copilots, workflow automations, or AI-enabled applications.

• Familiarity with Microsoft Copilot Studio, Power Platform, Power Automate, and connectors, or an equivalent platform.

• Experience in developing or integrating Azure solutions, encompassing identity, security, application hosting, data, integration, and monitoring services.

• Proficiency in developing, testing, debugging, and maintaining production-quality applications, APIs, integrations, and automation using Python and/or C#, REST APIs, JSON, scripting, and data integration technologies.

• Experience applying SDLC practices and delivering solutions across business, technology, security, compliance, and other cross-functional stakeholders.

• Strong fundamentals in software engineering, including maintainability, testing, error handling, security, reliability, and documentation.

• Working knowledge of LLMs, prompt engineering, grounding, RAG, agents, evaluations, and model limitations.

• Capability to design secure, scalable, observable, supportable, and cost-effective cloud solutions.

• Understanding of authentication, authorization, secrets management, data protection, networking, APIs, and enterprise integration patterns.

• Excellent analytical, troubleshooting, communication, presentation, and collaboration skills, including the ability to work effectively with non-technical stakeholders.

🏝️ Benefits

• Annual Performance Bonus

• Stock Purchase

• Medical Plans

• Prescription Drugs

• Dental

• Vision

• Family Assistance Program

• FSA

• HSA

• Pre-Tax Parking Plan

• 401(k)

• Life/AD&D

• Accident insurance

• Critical Illness insurance

• Hospital Indemnity

• Long Term Care

• Short-term Disability

• Long-term Disability

• Business Travel Accident

• Identity Theft protection

• Paid Time Off

• Flexible Work Options

• Paid Holidays

• Sabbatical

• Gift Matching

• Well-Being Stipend

• Personal and Professional Development

• Ownership business model / part ownership