AI Solutions Architect / AI Engineering Lead

LinkIt is seeking an experienced, hands-on AI Solutions Architect / AI Engineering Lead to join our remote team. Your primary business mission is to transform LinkIt's K-12 platform and build future products. You will solve critical educational data challenges by automating reporting pipelines, building intelligent workflow copilots, and integrating agentic Retrieval-Augmented Generation (RAG) architectures directly into our core benchmarks analysis and Multi-Tiered System of Supports (MTSS) workflows. Reporting to the platform's Senior AI Architecture Lead, you will design, architect, and build within a modern tech stack featuring Python, the .NET ecosystem, AWS, and GCP. You will leverage advanced orchestration frameworks such as LangChain or LlamaIndex, vector databases, and LLM provider APIs (e.g., OpenAI, Anthropic, Gemini).

The ideal candidate combines hands-on AI engineering expertise with strong architectural thinking, an understanding of business processes, and the ability to collaborate across technical and non-technical teams. In this dual role, you will act as both a thought leader shaping our AI architecture and a direct technical contributor executing implementation. You will help mature and scale LinkIt's emerging AI organization, establish best practices for reliable, production-grade AI systems, and bridge the gap between high-level strategy and technical execution.

This role partners closely with cross-functional leadership, product management, engineering, IT, operations, and external development partners to identify, architect, prioritize, and implement practical AI solutions that improve operational efficiency, scalability, customer experience, analytics, reporting, and product innovation., AI Strategy & Architecture

• Roadmap & Design: Help define and execute LinkIt's AI roadmap across both platform capabilities and internal operations, designing scalable, secure, and maintainable solutions aligned with business goals.
• Technology Evaluation: Evaluate emerging AI technologies, platforms, models, orchestration frameworks, and vendors to recommend appropriate infrastructure patterns that maximize ROI.
• Standards & Best Practices: Establish organizational standards, evaluation methodologies, and implementation guardrails for production-grade AI deployment.

-Hands-On Engineering & Feature Delivery

• Advanced RAG Deployment: Deploy Generative AI solutions using agentic Retrieval-Augmented Generation (RAG) architectures to design grounded AI features using trusted datasets.
• LLM Fine-Tuning: Execute targeted LLM fine-tuning on open-source or commercial models to accurately process domain-specific K-12 educational terminology, curriculum tracking data, and complex student assessment benchmarks.
• Prototype to Production: Rapidly transition exploratory AI pilots into robust, production-grade enterprise code, ensuring seamless integration into existing application layers.
• AI-Driven Velocity: Actively leverage next-generation AI coding assistant tools (e.g., GitHub Copilot, Claude Code) within your daily local environment to accelerate development velocity and model modern engineering best practices.

-MLOps, Security & Governance

• AI Model Monitoring: Implement robust MLOps practices and AI observability pipelines (utilizing tools such as LangSmith, Arize, or Phoenix) to actively mitigate model drift, reduce hallucinations, and ensure consistent output quality over time.
• System Trust & Security: Operationalize core AI Ethics & Compliance frameworks across all engineering workflows to guarantee that platform outputs maintain absolute data integrity, auditability, explainability, and strict multi-tenant data security.

-Operational Enablement & Cross-Functional Leadership

• Workflow Automation: Apply advanced prompt engineering workflows to design and implement highly reliable AI copilots, knowledge assistants, text summarization tools, and reporting enhancements that maximize multi-departmental productivity.
• Cross-Functional Collaboration: Partner with Product, Consulting, Customer Success, Sales, Marketing, Content, Operations, and IT teams to identify workflow automation opportunities and prioritize quick wins.
• Technical Oversight & Mentorship: Provide architectural guidance and technical oversight for internal AI initiatives, coordinating implementation standards across internal engineering teams and external development partners., * High Autonomy & Technical Ownership: We encourage our engineers to dive in and transform exploratory AI pilots into production-ready enterprise solutions. You will have technical ownership over selecting and tuning the right models, orchestration frameworks, and optimization patterns to build scalable, secure software that supports ongoing data collection and informed decision-making.
• A Collaborative, Elite Team Culture: You will never work in an isolated silo. You will work closely across an established internal AI engineering team, operations strategy leads, and cross-functional engineering resources to unify our implementation standards, tools, and execution strategies.
• Measurable, Real-World Impact: The code you write will directly empower educators to gather and interpret curriculum assessment data across multiple subject areas. Your AI integrations will immediately improve how districts monitor student performance, guide action planning, and implement targeted intervention support.

Do you have experience in UX implementation?, * Core Software Engineering: 5+ years of professional experience in software engineering, platform engineering, or modern application design.

• Generative AI Expertise: 2+ years of direct, hands-on experience building, deploying, and integrating Large Language Model (LLM) solutions within production-grade software.
• Language Proficiency: Strong, practical backend development capabilities working fluently inside Python and/or the .NET ecosystem.
• Architecture Fundamentals: Strong understanding of APIs, integrations, data architecture, cloud infrastructures (AWS/GCP), and modern application design patterns.
• Advanced AI Patterns: Deep technical understanding of agentic orchestration pipelines, prompt engineering workflows, RAG configurations, and context lake management.
• AI Tooling Native: Fluent, active daily utilization of cutting-edge AI coding assistants (such as Copilot or Claude Code) with a clear philosophy on maximizing clean software output using AI.
• Collaboration & Communication: Exceptional communication skills with the verified ability to translate abstract business problems into technical solutions and work effectively with both technical and operational teams.
• AI Expertise: Well-versed in modern AI platforms, tools, and capabilities, with a strong understanding of AI best practices, standardized implementation patterns, prompt and workflow design, and the principles of effective AI user experience (AI UX) and user interface design (AI UI) to drive adoption, usability, and business value.

-Preferred (Nice-to-Have)

• Vector Architecture: Direct experience navigating vector databases, implementing embedding strategies, and connecting to commercial APIs (OpenAI, Anthropic, Gemini).
• AI Governance Ecosystem: Experience with AI observability, governance, and validation tools (e.g., LangSmith, Arize, Phoenix).
• Multimodal AI: Familiarity with Multimodal AI patterns to evaluate charts, graphs, formatted student test sheets, or structured visual educational materials.
• Industry Domain: Prior experience building analytics, reporting tools, or workflow automation solutions for SaaS platforms, educational technology, or highly security-conscious compliance environments.
• Collaboration Tools: Familiarity with the Google Workspace ecosystem for internal operational integration.

3.33.3 out of 5 stars Remote $140,000 - $160,000 a year - Full-time, Pulled from the full job description

• Health insurance
• Paid time off
• Vision insurance
• Dental insurance
• Paid holidays, * Compensation: Target compensation $140,000 - $160,000 depending on experience. Eligible for annual performance-based bonus
• Benefits such as vacation, holiday pay, and health insurance
• Location: 100% fully remote or Hybrid New York City Office
• Must be authorized to work in the U.S. without sponsorship

Pay: $140,000.00 - $160,000.00 per year

Benefits:

• Dental insurance
• Health insurance
• Paid time off
• Vision insurance

Linklt is a leader in K-12 data-driven technology solutions and consulting services. We help schools streamline the collection, management, and analysis of student performance data to improve academic outcomes and educator productivity. Specifically, our data warehouse and assessment platform enable schools to store and analyze both third-party and locally created data for all grade levels and subject areas. Linklt also provides custom analytical services to help educators build capacity to lead effectively, add structure to data analysis, and simplify compliance and data-centric processes. Our MTSS solution streamlines workflows, fosters consistency, and measures ROI through student progress monitoring and implementation fidelity dashboards. Lastly, through our Magnolia Consulting division, our team of expert consultants integrates strategy, product, and process into structured systems that drive sustainable change. Customized supports include MTSS, special programs, literacy, mental health, whole-child, and more. At LinkIt, we come to work every day knowing that our work has a direct impact on students, teachers, and their ability to succeed. While we differentiate our products through their comprehensiveness, ease of use, and innovation, our unique value proposition is our relentless focus on customer service and support. For more about us, please visit linkit.com.