AI Product Engineer (Full Stack)

AI Product Engineer (Full Stack)AI/LLM Integration, Full-Stack Development & Product Engineering | Remote | U.S. HoursPosition Type: Full-Time, Remote Working Hours: U.S. Business HoursAbout the RoleAt Pavago, one of our clients is hiring an AI Product Engineer (Full Stack) to build and scale a production-ready web application from the ground up.This is a hands-on product engineering role, not a support or maintenance position.You’ll take ownership across the entire product lifecycle:Frontend developmentBackend architectureAI/LLM integrationAPIs and data infrastructureAuthentication and securityDeployment and performanceProduct iteration and scalingYou’ll work closely with leadership to turn product ideas into working, production-ready software, ship quickly, learn from real usage, and continuously improve the platform.If you’re a builder who can independently take an AI-powered product from concept → MVP → production → scale, this role is a strong fit.What You’ll OwnFull-Stack Product Development — End-to-EndOwn development of the product from initial architecture through production deployment.You’ll:Build and launch a production-ready web applicationOwn both frontend and backend developmentDesign intuitive, responsive product experiencesBuild scalable application architectureTranslate product requirements into working featuresDeploy, monitor, and improve the applicationContinuously iterate after launch based on user feedback and product needsThis role requires someone comfortable owning the entire technical product, rather than working within one narrow layer of the stack.AI & LLM IntegrationDesign AI functionality that solves real product problems—not AI features added simply for novelty.You’ll:Integrate LLMs such as Claude or similar modelsDesign AI-powered product workflowsBuild reliable interactions between LLMs, application logic, and user dataStructure prompts and outputs for consistent product behaviorHandle edge cases and model failuresImplement safeguards and validation around AI-generated outputsYou should understand practical LLM limitations, including:HallucinationsUnreliable outputsContext limitationsEdge casesFailure handlingThe goal is to build AI experiences users can actually rely on in production.Backend Systems, APIs & Data InfrastructureBuild and manage backend infrastructure using Supabase or similar platforms.You’ll:Design scalable APIsBuild efficient data models and structuresManage application data and backend logicConnect frontend experiences to backend servicesIntegrate external APIs and AI servicesOptimize database queries and application performanceBuild infrastructure capable of supporting continued product growthSecurity, Authentication & PermissionsBuild security into the product from the beginning.Implement and maintain:AuthenticationUser permissionsAuthorization logicData access controlsSecure API interactionsData protection practicesEnsure sensitive information is handled appropriately and that users only have access to the functionality and data they are authorized to use.AI Agents & AutomationWhere appropriate, build more advanced AI-powered systems such as:AI agentsMulti-step AI workflowsAutomated operational processesTool-calling workflowsAI-assisted decision systemsDesign these systems with appropriate validation and safeguards so automation remains reliable in real-world scenarios.Product Collaboration & Rapid IterationWork directly with leadership to translate ideas into technical solutions.You’ll:Understand product requirements and business objectivesRecommend practical technical approachesBuild prototypes quicklyTurn successful prototypes into production featuresShip frequentlyGather feedbackRefine functionality based on actual usageBalance speed with long-term maintainabilityYou should be comfortable operating where product requirements evolve and engineers are expected to contribute to how a problem should be solved, not simply execute tickets.Debugging, Performance & ReliabilityOwn product quality after features are shipped.You’ll:Diagnose and resolve bugsMonitor system behaviorImprove application performanceIdentify technical bottlenecksStrengthen system reliabilityImprove user experience based on production issuesReduce technical debt as the platform maturesRequired Experience & SkillsNon-NegotiablesStrong full-stack engineering experience across frontend and backend developmentProven experience building and shipping production-level productsHands-on experience integrating AI/LLMs into real applicationsStrong understanding of:System architectureAPI designData structuresApplication performanceExperience with Supabase or similar backend platformsUnderstanding of practical AI limitations, including:HallucinationsFailure statesEdge casesOutput validationStrong knowledge of security best practices, including:AuthenticationPermissionsData protectionStrong debugging and problem-solving abilityAbility to work independently and take end-to-end ownership of product developmentNice to HaveExperience building AI agentsExperience designing AI automation workflowsFamiliarity with Claude or similar LLMs in productionExperience building:SaaS productsOperational platformsWorkflow applicationsExperience taking products from MVP to productionExperience scaling applications after initial launchExposure to:AviationLogisticsMembership systemsWhat Makes You a Strong FitYou:Are a builder, not just a feature contributorCan take an idea and independently turn it into working softwareThink across frontend, backend, data, AI, security, and infrastructureHave shipped real products that users depend onUnderstand that production AI requires more than calling an LLM APIDesign around AI failure modes rather than assuming outputs will always be correctMove quickly while maintaining strong engineering standardsDebug problems independentlyMake thoughtful architecture decisions without overengineeringEnjoy working directly with leadership and translating business ideas into productsTake ownership from initial concept through production performanceWhat a Typical Day Looks LikeYour day may include:Building a new frontend product experienceDesigning backend logic and database structuresIntegrating an LLM into a product workflowImproving prompts, validation, or AI guardrailsBuilding APIs connecting product componentsConfiguring authentication and permissionsDebugging an issue discovered in productionReviewing system performance and reliabilityDiscussing a new product idea with leadershipRapidly prototyping a solutionShipping a feature and monitoring how users interact with itImproving architecture as product usage growsIn short: you own the engineering behind an AI-powered product from idea to production and continuously make it faster, smarter, safer, and more scalable.Key Metrics for SuccessSuccessful launch of a production-ready applicationSpeed and consistency of feature deliverySystem stability and reliabilityApplication performanceQuality and usefulness of AI integrationsEffective handling of AI errors and edge casesReduction in bugs and recurring production issuesScalability of application architectureMaintainability and quality of the codebaseAbility to iterate rapidly based on real product feedbackWhy This Role Stands OutBuild an AI-powered product from the ground upEnd-to-end ownership across the full technology stackDirect involvement in product and architecture decisionsHands-on exposure to production LLM systemsOpportunity to build AI workflows and agents around real-world use casesWork directly with leadershipHigh autonomy and execution ownershipOpportunity to take a product from MVP through production and scaleFully remote environmentInterview ProcessInitial Screening CallTechnical & Systems Design InterviewPractical Task – Product Build / AI Integration ScenarioFinal InterviewInternal Review & ApprovalOffer & OnboardingApply NowIf you:Are a strong full-stack engineerHave built and shipped real production productsHave hands-on experience integrating LLMs into applicationsUnderstand AI hallucinations, edge cases, and guardrailsCan independently own frontend, backend, APIs, and infrastructureEnjoy building products from zero rather than simply maintaining existing systemsWe’d love to hear from you.Important: Spark Hire Video InterviewAs part of our application process, qualified candidates will be invited to complete a one-way video interview through Spark Hire.This is your opportunity to introduce yourself and highlight your experience with full-stack product development, production AI/LLM integrations, system architecture, APIs, Supabase or similar backend platforms, security, and product ownership.We recommend discussing a product you have personally built and shipped, including your specific technical contribution, the architecture you chose, how AI was integrated, how you handled hallucinations or failure states, and how you took the system from initial development into production.Please complete your Spark Hire interview promptly after receiving the invitation. Candidates who do not complete the video interview may not move forward in the hiring process.#AIProductEngineer #FullStackEngineer #AIEngineer #SoftwareEngineer #FullStackDeveloper #LLM #GenerativeAI #ClaudeAI #Supabase #SaaS #AIApplications #ProductEngineering #RemoteDeveloper #RemoteJobs #TechJobs #LI-AG1

AI Product Engineer (Full Stack)

AI/LLM Integration, Full-Stack Development & Product Engineering | Remote | U.S. Hours

Position Type: Full-Time, Remote
Working Hours: U.S. Business Hours

About the Role

At Pavago, one of our clients is hiring an AI Product Engineer (Full Stack) to build and scale a production-ready web application from the ground up.

This is a hands-on product engineering role, not a support or maintenance position.

You’ll take ownership across the entire product lifecycle:

• Frontend development
• Backend architecture
• AI/LLM integration
• APIs and data infrastructure
• Authentication and security
• Deployment and performance
• Product iteration and scaling

You’ll work closely with leadership to turn product ideas into working, production-ready software, ship quickly, learn from real usage, and continuously improve the platform.

If you’re a builder who can independently take an AI-powered product from concept → MVP → production → scale, this role is a strong fit.

What You’ll Own

Full-Stack Product Development — End-to-End

Own development of the product from initial architecture through production deployment.

You’ll:

• Build and launch a production-ready web application
• Own both frontend and backend development
• Design intuitive, responsive product experiences
• Build scalable application architecture
• Translate product requirements into working features
• Deploy, monitor, and improve the application
• Continuously iterate after launch based on user feedback and product needs

This role requires someone comfortable owning the entire technical product, rather than working within one narrow layer of the stack.

AI & LLM Integration

Design AI functionality that solves real product problems—not AI features added simply for novelty.

You’ll:

• Integrate LLMs such as Claude or similar models
• Design AI-powered product workflows
• Build reliable interactions between LLMs, application logic, and user data
• Structure prompts and outputs for consistent product behavior
• Handle edge cases and model failures
• Implement safeguards and validation around AI-generated outputs

You should understand practical LLM limitations, including:

• Hallucinations
• Unreliable outputs
• Context limitations
• Edge cases
• Failure handling

The goal is to build AI experiences users can actually rely on in production.

Backend Systems, APIs & Data Infrastructure

Build and manage backend infrastructure using Supabase or similar platforms.

You’ll:

• Design scalable APIs
• Build efficient data models and structures
• Manage application data and backend logic
• Connect frontend experiences to backend services
• Integrate external APIs and AI services
• Optimize database queries and application performance
• Build infrastructure capable of supporting continued product growth

Security, Authentication & Permissions

Build security into the product from the beginning.

Implement and maintain:

• Authentication
• User permissions
• Authorization logic
• Data access controls
• Secure API interactions
• Data protection practices

Ensure sensitive information is handled appropriately and that users only have access to the functionality and data they are authorized to use.

AI Agents & Automation

Where appropriate, build more advanced AI-powered systems such as:

• AI agents
• Multi-step AI workflows
• Automated operational processes
• Tool-calling workflows
• AI-assisted decision systems

Design these systems with appropriate validation and safeguards so automation remains reliable in real-world scenarios.

Product Collaboration & Rapid Iteration

Work directly with leadership to translate ideas into technical solutions.

You’ll:

• Understand product requirements and business objectives
• Recommend practical technical approaches
• Build prototypes quickly
• Turn successful prototypes into production features
• Ship frequently
• Gather feedback
• Refine functionality based on actual usage
• Balance speed with long-term maintainability

You should be comfortable operating where product requirements evolve and engineers are expected to contribute to how a problem should be solved, not simply execute tickets.

Debugging, Performance & Reliability

Own product quality after features are shipped.

You’ll:

• Diagnose and resolve bugs
• Monitor system behavior
• Improve application performance
• Identify technical bottlenecks
• Strengthen system reliability
• Improve user experience based on production issues
• Reduce technical debt as the platform matures

Required Experience & Skills

Non-Negotiables

• Strong full-stack engineering experience across frontend and backend development
• Proven experience building and shipping production-level products
• Hands-on experience integrating AI/LLMs into real applications
• Strong understanding of:
• System architecture
• API design
• Data structures
• Application performance
• Experience with Supabase or similar backend platforms
• Understanding of practical AI limitations, including:
• Hallucinations
• Failure states
• Edge cases
• Output validation
• Strong knowledge of security best practices, including:
• Authentication
• Permissions
• Data protection
• Strong debugging and problem-solving ability
• Ability to work independently and take end-to-end ownership of product development

Nice to Have

• Experience building AI agents
• Experience designing AI automation workflows
• Familiarity with Claude or similar LLMs in production
• Experience building:
• SaaS products
• Operational platforms
• Workflow applications
• Experience taking products from MVP to production
• Experience scaling applications after initial launch
• Exposure to:
• Aviation
• Logistics
• Membership systems

What Makes You a Strong Fit

You:

• Are a builder, not just a feature contributor
• Can take an idea and independently turn it into working software
• Think across frontend, backend, data, AI, security, and infrastructure
• Have shipped real products that users depend on
• Understand that production AI requires more than calling an LLM API
• Design around AI failure modes rather than assuming outputs will always be correct
• Move quickly while maintaining strong engineering standards
• Debug problems independently
• Make thoughtful architecture decisions without overengineering
• Enjoy working directly with leadership and translating business ideas into products
• Take ownership from initial concept through production performance

What a Typical Day Looks Like

Your day may include:

• Building a new frontend product experience
• Designing backend logic and database structures
• Integrating an LLM into a product workflow
• Improving prompts, validation, or AI guardrails
• Building APIs connecting product components
• Configuring authentication and permissions
• Debugging an issue discovered in production
• Reviewing system performance and reliability
• Discussing a new product idea with leadership
• Rapidly prototyping a solution
• Shipping a feature and monitoring how users interact with it
• Improving architecture as product usage grows

In short: you own the engineering behind an AI-powered product from idea to production and continuously make it faster, smarter, safer, and more scalable.

Key Metrics for Success

• Successful launch of a production-ready application
• Speed and consistency of feature delivery
• System stability and reliability
• Application performance
• Quality and usefulness of AI integrations
• Effective handling of AI errors and edge cases
• Reduction in bugs and recurring production issues
• Scalability of application architecture
• Maintainability and quality of the codebase
• Ability to iterate rapidly based on real product feedback

Why This Role Stands Out

• Build an AI-powered product from the ground up
• End-to-end ownership across the full technology stack
• Direct involvement in product and architecture decisions
• Hands-on exposure to production LLM systems
• Opportunity to build AI workflows and agents around real-world use cases
• Work directly with leadership
• High autonomy and execution ownership
• Opportunity to take a product from MVP through production and scale
• Fully remote environment

Interview Process

1. Initial Screening Call
2. Technical & Systems Design Interview
3. Practical Task – Product Build / AI Integration Scenario
4. Final Interview
5. Internal Review & Approval
6. Offer & Onboarding

Apply Now

If you:

• Are a strong full-stack engineer
• Have built and shipped real production products
• Have hands-on experience integrating LLMs into applications
• Understand AI hallucinations, edge cases, and guardrails
• Can independently own frontend, backend, APIs, and infrastructure
• Enjoy building products from zero rather than simply maintaining existing systems

We’d love to hear from you.

Important: Spark Hire Video Interview

As part of our application process, qualified candidates will be invited to complete a one-way video interview through Spark Hire.

This is your opportunity to introduce yourself and highlight your experience with full-stack product development, production AI/LLM integrations, system architecture, APIs, Supabase or similar backend platforms, security, and product ownership.

We recommend discussing a product you have personally built and shipped, including your specific technical contribution, the architecture you chose, how AI was integrated, how you handled hallucinations or failure states, and how you took the system from initial development into production.

Please complete your Spark Hire interview promptly after receiving the invitation. Candidates who do not complete the video interview may not move forward in the hiring process.

#AIProductEngineer #FullStackEngineer #AIEngineer #SoftwareEngineer #FullStackDeveloper #LLM #GenerativeAI #ClaudeAI #Supabase #SaaS #AIApplications #ProductEngineering #RemoteDeveloper #RemoteJobs #TechJobs #LI-AG1

Pavago - Connecting You to Global Remote Opportunities 🌍At Pavago, we redefine the boundaries of talent recruitment. Dive into a world where your geographical location doesn't restrict your career aspirations. As a distinguished international recruitment agency, we specialize in connecting remote talents with companies eager to tap into global expertise.🌟 Why Consider Opportunities Through Pavago?Competitive Pay: Command the salary you deserve, regardless of where you reside.Broad Horizons: Unlock a wide array of remote positions spanning diverse industries and regions.Skill Enrichment: Work alongside international teams, contribute your unique insights, and amplify your career trajectory.Whether you're a seasoned professional hunting for a novel global venture or a budding talent keen on leaving an international imprint, Pavago is your conduit to businesses that appreciate and seek out worldwide perspectives.Embrace a realm where opportunities transcend borders. Together, let's pioneer the next era of remote work. 🚀Explore global opportunities with us today!"

Pavago - Connecting You to Global Remote Opportunities 🌍

At Pavago, we redefine the boundaries of talent recruitment. Dive into a world where your geographical location doesn't restrict your career aspirations. As a distinguished international recruitment agency, we specialize in connecting remote talents with companies eager to tap into global expertise.

🌟 Why Consider Opportunities Through Pavago?

Competitive Pay: Command the salary you deserve, regardless of where you reside.

Broad Horizons: Unlock a wide array of remote positions spanning diverse industries and regions.

Skill Enrichment: Work alongside international teams, contribute your unique insights, and amplify your career trajectory.

Whether you're a seasoned professional hunting for a novel global venture or a budding talent keen on leaving an international imprint, Pavago is your conduit to businesses that appreciate and seek out worldwide perspectives.

Embrace a realm where opportunities transcend borders. Together, let's pioneer the next era of remote work. 🚀

Explore global opportunities with us today!"