Artificial Intelligence Remote Jobs in Vermont (US)
This page tracks remote artificial intelligence openings that are location-eligible for Vermont.
This page tracks remote artificial intelligence openings that are location-eligible for Vermont.
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$10 - $151,080
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3088 Jobs
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Top 35 business advisory and CPA firm helping clients and team members achieve what's next.
• Own the product vision, roadmap, and backlog for assigned AI platforms across various Aprio business lines. • Translate complex domain and practice requirements into clear, actionable user stories, acceptance criteria, and product specifications. • Lead the full development lifecycle — scoping, sprint planning, QA, and rollout — coordinating onshore and offshore development resources. • Work closely with Engineering, tax accountants, and other cross functions to deliver and improve the platforms. • Prioritize features and balance near-term delivery with long-term platform scalability and maintainability. • Run structured requirements-gathering sessions with subject matter experts across the relevant practice or business area. • Communicate project status, risks, and decisions clearly to practitioners and firm leadership. • Serve as the primary point of contact for assigned platforms, owning outcomes with transparency. • Apply generative-AI capabilities relevant to professional services — LLMs, document intelligence, agentic workflows, and structured output generation. • Test and validate AI models, APIs, and tooling (e.g., Anthropic Claude, OpenAI, Azure AI) for integration into Aprio's platforms. • Support responsible AI practices, including data privacy, data residency, and client confidentiality considerations (e.g., §7216 consent where applicable).
Role Description We're looking for a Workflow Engineer who turns AI capabilities into production-grade agent workflows that automate real business processes. You'll design and ship LLM-powered flows, from RAG pipelines and MCP tools to multi-step agentic automations, and integrate them safely with our apps, data, and APIs. You'll work closely with product, platform, and security to deliver fast, reliable, and cost-efficient AI outcomes. Essential Duties & Responsibilities: - Build agentic systems - Design and implement agent workflows using tools like LangGraph, CrewAI, n8n (or similar) - Create task decomposition, tool-use policies, guardrails, and evaluation loops - Implement Retrieval-Augmented Generation (RAG) - Stand up vector search and retrieval pipelines; select embedding strategies - Optimize context packing, grounding quality, and hallucination mitigation - Develop MCP tools & integrations - Build Model Context Protocol (MCP) servers and custom tools to safely connect to APIs, databases, and internal systems - Establish capabilities, permissions, and auditing for tool use - Ship production-ready AI services - Build FastAPI/Node services that expose AI workflows behind secure APIs - Own CI/CD for workflow services; write tests, contract checks, and evals - Instrument workflows with latency, cost, accuracy, and safety metrics - Run prompt/eval experiments; iterate on prompts, memory, and grounding - Work with product & ops to prioritize use cases - Collaborate with Platform/DevOps to deploy and scale reliably in Kubernetes Qualifications - Strong coding in Python and/or Node; clean API design - Hands-on with LLM integration (prompting, tool use, function calling) - Experience building RAG systems and working with vector databases - Practical familiarity with LangGraph/CrewAI/n8n or similar orchestration - Experience building MCP tools/servers or equivalent agent-tool frameworks - Solid understanding of REST/GraphQL, auth (OAuth/OIDC), and secure integration - Containers, Git, CI/CD basics; comfort shipping production services Preferred Qualifications - Evals & guardrails (e.g., structured output, JSON schemas, toxicity/PII checks) - Knowledge graphs / event-driven architectures/workflow engines - Model selection & optimization; prompt caching; cost/perf tuning - Exposure to LLM safety, privacy, governance, and enterprise compliance Additional Details - Potential Salary Range: $115,000 to $120,000. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. - This role is eligible for remote US-based (work-from-home) locations. Chicago-based candidates would work in a hybrid capacity from Accertify's HQ in Itasca, IL. - Visa Sponsorship: Employment eligibility to work for Accertify in the U.S. is required, as Accertify will not pursue Visa sponsorship for this position. Benefits - Comprehensive benefits package, including medical, dental, and vision coverage - Paid time off - Wellness programs - Participation in retirement programs, including a 401(k) plan with company matching contributions, subject to plan terms and eligibility requirements
At Point C Health, we know we are better together. We value, respect, and protect the uniqueness each of us brings. Innovation flourishes by including all voices and makes our business—and our society—stronger. Point C Health is an equal opportunity employer and we are committed to providing equal opportunity in all of our employment practices, including selection, hiring, performance management, promotion, transfer, compensation, benefits, education, training, social, and recreational activities to all persons regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, genetic information, pregnancy, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, and military and veteran status, or any other protected status protected by local, state or federal law.
• Partner with clinical and utilization management teams to understand workflows, data needs, and areas where analysis can improve decision-making and outcomes • Use AI tools to accelerate data pulls and surface patterns across large clinical datasets • Analyze AI findings to flag trends or anomalies that may not be immediately visible through manual review • Leverage AI to support documentation tasks such as drafting summaries, structuring findings, and generating repeatable templates for clinical and operational use • Pull, clean, and analyze healthcare data including claims, date of service, provider specialty, utilization patterns, and clinical indicators • Identify trends and draw actionable insights from clinical and utilization data to support care management, cost containment, and quality improvement efforts • Support the clinical team in understanding benefit structures, plan designs, and how they interact with utilization and outcomes data • Identify opportunities where AI or automation could streamline clinical review processes, flag outliers, or reduce manual workload for clinical staff • Build lightweight data tools, dashboards, or summary reports to make clinical and utilization data more accessible and actionable • Document findings, methodologies, and recommendations clearly so insights are repeatable and usable beyond the internship • Present data findings and recommendations to clinical and operational leadership in a clear, accessible format
En Inlaze creemos en el talento sin etiquetas y en construir equipos donde todos tengamos las mismas oportunidades.
Role Description Construir, mantener y escalar las automatizaciones, integraciones y las herramientas internas que las soportan — eliminando trabajo manual, reduciendo pérdidas operativas y aumentando la velocidad de decisión en toda Inlaze. Es un rol full-stack pragmático: backend (Node/TS + N8N + agentes IA) y frontend de herramientas internas y back-offices (React/Next.js). Construyes lo que el equipo usa todos los días. Qualifications - Node.js + TypeScript a nivel de desarrollo real (no scripts básicos). - React/Next.js para construir herramientas internas, paneles y back-offices — el rol construye UIs. - N8N avanzado: flujos complejos, webhooks e integración de APIs. - Integración de APIs REST: auth, manejo de errores, paginación y rate limits. - Bases de datos relacionales: modelar y escribir datos desde lo que construyes. Requirements - Construir herramientas internas, paneles y back-offices en React/Next.js que el equipo opera sin tocar código. - Diseñar y mantener automatizaciones e integraciones con N8N y Node.js/TypeScript. - Construir y escalar agentes de IA confiables dentro de procesos reales del negocio. - Integrar APIs externas gestionando autenticación, errores, rate limits y paginación. - Monitorear automatizaciones en producción y resolver incidentes con autonomía técnica. Benefits - 100% remoto. - Contrato como contractor. - Fee en USD según experiencia y conocimientos. - Programa de referidos de empleados. - 1 día completo para celebrar tu cumpleaños. - Acceso libre a Udemy.
Role Description Lead Cloud & AI Security Strategy: Own and execute the strategic vision, roadmap, and operating model for Ascension's Cloud Security and AI Security programs under the Senior Director, driving secure adoption of cloud and AI technologies through risk-based priorities, measurable outcomes, and alignment with enterprise objectives. Build and Develop High-Performing Teams: Lead, coach, and inspire Cloud Security and AI Security teams while establishing scalable operating models, conducting capacity and workforce planning, optimizing team processes, and fostering a culture of accountability, collaboration, adaptability, and continuous learning. Develop talent, strengthen organizational capabilities, and ensure the teams are positioned to effectively support evolving business, technology, and security needs. Drive Security Technology Strategy & Program Transformation: Develop and manage the Cloud Security & AI Security technology roadmap, including capability planning, technology evaluation, vendor selection, and oversight of implementations such as CNAPP, AI security controls, and automation capabilities. Advance Secure Cloud & AI Enablement: Partner across technology, architecture, engineering, governance, legal, and business teams to establish security standards, risk management practices, and control requirements that enable innovation while protecting Ascension's cloud environments and AI solutions. Measure, Communicate, and Advance Security Outcomes: Establish program metrics, key performance indicators, executive reporting, and strategic points of view to communicate risk, security posture, priorities, and program value. Develop and deliver presentations to senior management to support decision-making and drive alignment across the enterprise. Qualifications - High School diploma equivalency with 3 years of cumulative experience OR Associate's degree/Bachelor's degree with 2 years of cumulative experience OR 7 years of applicable cumulative job specific experience required. - 3 years of leadership or management experience preferred. - Prior cybersecurity consulting experience strongly preferred, particularly with a Big Four consulting firm or equivalent strategic advisory experience. - 8+ years of cybersecurity experience with progressive leadership responsibilities, including direct people management. - Experience building or maturing AI security, AI governance, or related programs. - Strong understanding of cloud security architectures, security controls, Identity and Access Management (IAM), and enterprise risk management principles. - Experience leading enterprise-scale security technology implementations and transformations, such as CNAPP solutions. - Relevant industry certifications such as CISSP, CCSP, or equivalent certifications preferred. Benefits - Paid time off (PTO) - Various health insurance options & wellness plans - Retirement benefits including employer match plans - Long-term & short-term disability - Employee assistance programs (EAP) - Parental leave & adoption assistance - Tuition reimbursement - Ways to give back to your community
Best-in-class fulfillment solution for ecommerce brands.
• Own the full product loop independently: AI-augmented discovery → story/spec → prototype → production PR → outcome measurement. You are accountable for the outcome, not just the handoff. • Independently conduct customer discovery and use AI tools to synthesize research across tickets, interviews, behavioral data, and competitive signals. • Demonstrate deep functional and technical knowledge of owned products end-to-end. Independently demo to merchants and partners; understand competitive landscape and key differentiators. • Use AI tools independently to analyze product metrics, identify usage patterns, and surface anomalies. Define success metrics and kill thresholds at spec time without coaching. • Maintain a prioritized automation roadmap ranked by impact × speed. Use AI tools to synthesize competitive intelligence, market trends, emerging warehouse automation capabilities, and customer insight into strategic inputs. • Identify the highest-leverage productivity and quality opportunities in ShipBob’s fulfillment operations. Evaluate automation hardware options, recommend the right strategic fit, and own the WMS-side product work that integrates them into the floor. • Independently evaluate whether a proposed solution fits ShipBob's architecture without Engineering translation. Understand service boundaries, data structures, and how merchant and partner API usage shapes data contracts. • Independently route changes through prototype-then-PR. Write clear story/specs and review AI-generated code before raising. PR promotion rate improves consistently. • Set experiment hypotheses with explicit kill thresholds. Make day-7 rollout/kill decisions on AI-surfaced data. • Additional duties and responsibilities as necessary.
• Own the full product loop end-to-end: AI-augmented discovery → story/spec → prototype → production PR → outcome measurement. You are accountable for the outcome, not just the handoff. • Own ShipBob's MCP server and merchant-facing chat capabilities end-to-end. Define the agent surface, ship the integrations, measure adoption. • Run customer discovery yourself; use AI tools to synthesize research across tickets, interviews, behavioral data, and competitive signals. • Demonstrate deep functional and technical knowledge of owned products end-to-end. Demo to merchants and partners yourself; understand competitive landscape and key differentiators. • Use AI tools to analyze product metrics, identify usage patterns, and surface anomalies. Define success metrics and kill thresholds at spec time — without coaching. • Maintain a prioritized roadmap ranked by impact × speed. Use AI tools to synthesize competitive intelligence, market trends, and customer insight into strategic inputs. • Evaluate whether a proposed solution fits ShipBob’s architecture without Engineering translation. Understand service boundaries, data structures, and how merchant and partner API usage shapes data contracts. • Route changes through prototype-then-PR. Write clear story/specs and review AI-generated code before raising. PR promotion rate improves consistently. • Set experiment hypotheses with explicit kill thresholds. Make day-7 rollout/kill decisions on AI-surfaced data. • Participate in architecture reviews alongside Engineering as the product judgment seat — the person making the build-vs-buy-vs-defer call on the room’s behalf. • Additional duties and responsibilities as necessary. • Your first 90 days: • Days 1–30 — Map the domain. Understand the ShipBob operating and commercial mode, examine the ODM codebase, anchor on the purpose and value of the domain, and stakeholder conversations to triangulate the top three active bets. Demo a throwaway prototype back to the pod. • Days 30–60 — Ship your first PR. Small and safe is fine. The point is proving the loop, not the size of the change. • Days 60–90 — Make a real call. Define and instrument the metric for one real bet, with the kill threshold set at spec time. Make at least one rollout-or-kill call on the data, in front of the team.
• Research and evaluate emerging AI technologies and automation opportunities. • Deploy, optimize, and maintain AI models, workflows, and business automation solutions. • Identify opportunities to improve operational efficiency through AI and automation. • Integrate business systems, APIs, and third-party applications. • Develop and maintain automated workflows and data pipelines. • Ensure seamless data flow and synchronization across platforms. • Manage AWS-hosted applications and cloud infrastructure. • Maintain PostgreSQL and other business-critical databases. • Support database performance, reliability, and data integrity. • Create and maintain dashboards and reports using Power BI, Looker Studio, or similar tools. • Transform operational and business data into actionable insights. • Monitor, troubleshoot, and optimize applications, integrations, and AI systems. • Document technical processes, workflows, and system configurations. • Provide technical support and guidance to internal teams.
Be a key player in crafting the high-quality data essential for AI innovation. Perfect for aspiring freelancers
Role Description Buscamos personas para grabar actividades cotidianas desde una perspectiva en primera persona utilizando una aplicación móvil. Puedes grabar tareas que ya realizas normalmente, como: - Cocinar - Limpiar - Doblar ropa - Ordenar espacios - Hacer jardinería - Pasear al perro Los videos ayudan a entrenar sistemas de IA y robótica para comprender cómo las personas interactúan con el mundo real. Qualifications - No se requiere experiencia previa. Requirements - iPhone 16/17, Google Pixel 6+ o Samsung Galaxy S21+ o superior - Acceso a internet - Nivel básico de inglés para registrarte y utilizar la plataforma Benefits - Horarios flexibles - Trabajo remoto por proyecto - USD $10 por hora de contenido aprobado - Bono adicional por la primera hora aprobada
Best-in-class fulfillment solution for ecommerce brands.
• Own the full product loop independently: AI-augmented discovery → story/spec → prototype → production PR → outcome measurement. You are accountable for the outcome, not just the handoff. • Conduct customer discovery and use AI tools to synthesize research across tickets, interviews, behavioral data, and competitive signals. • Demonstrate deep functional and technical knowledge of owned products end-to-end. Demo to merchants and partners; understand competitive landscape and key differentiators. • Use AI tools to analyze product metrics, identify usage patterns, and surface anomalies. Define success metrics and kill thresholds at spec time without coaching. • Maintain a prioritized roadmap ranked by impact × speed. Use AI tools to synthesize competitive intelligence, market trends, and customer insight into strategic inputs. • Evaluate whether a proposed solution fits ShipBob's architecture without Engineering translation. Understand service boundaries, data structures, and how merchant and partner API usage shapes data contracts. • Route changes through prototype-then-PR. Write clear story/specs and review AI-generated code before raising. PR promotion rate improves consistently. • Set experiment hypotheses with explicit kill thresholds. Make day-7 rollout/kill decisions on AI-surfaced data. • Additional duties and responsibilities as necessary. • You'll apply this builder model to one of ShipBob's most operationally critical product surfaces – Sortation Technology. • Translate merchant, marketplace, and channel requirements into sortation capabilities across the fulfillment lifecycle. Sortation performance shapes outcomes for DTC, marketplace, B2B/retail, and returns flows: on-time shipping, marketplace and retailer routing-guide compliance, inventory accuracy, and accurate returns disposition. Sequence the roadmap around the highest-impact pain points. • Close the gap between system signals and physical reality across every sortation surface. Sortation failures show up as merchant-visible defects: late shipments, mis-sorts, missing tracking events, mis-routed returns, and inventory inaccuracy at stowing. Build the tooling, workflows, and verification signals that prevent them. • Partner with Operations to turn product into adoption. Work directly with FC, Sort Center, Inbound, and Returns leadership, alongside Process Engineering and Transportation. Translate new tools into standard operating procedures and measurable performance improvement across every sortation surface — from manual sort to future automated unit sorters. • Move the metrics that define sortation performance — outbound execution SLAs (Click-to-Collect, Mis-sort Rate, Container Audit Defect Rate), inbound rebuild outcomes (drop-to-stock, SLA adherence), B2B compliance (SLA, load accuracy, retailer routing-guide compliance), and returns processing (cycle time, disposition accuracy).
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