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Full-Stack AI Engineer at Pavago · ApplyPick

Jobs
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Pavago
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Full-Stack AI Engineer

Full-Stack AI Engineer

PavagoAfghanistan, Åland Islands + 193 more

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Full-Stack AI Engineer Position Type: Full-Time, Remote Working Hours: U.S. Business Hours Location: Remote (LATAM, Eastern Europe, Pakistan, India, South Africa Preferred)

About the Role

We are hiring a highly skilled Full-Stack AI Engineer to build, deploy, and scale AI-powered applications that solve real business problems.

This role combines full-stack software engineering with applied AI/ML expertise. You will work across backend systems, AI pipelines, APIs, cloud infrastructure, and frontend applications to bring AI features from prototype to production.

The ideal candidate is both technically strong and product-minded — someone who can move quickly, build scalable systems, and turn modern AI capabilities into reliable, user-friendly products.

You will collaborate closely with engineering, product, and data teams to deliver AI-powered workflows, intelligent automation systems, chat experiences, analytics tools, and scalable machine learning infrastructure.

What You’ll Own

AI & LLM Integration
Deploy and integrate AI/ML models using OpenAI, Hugging Face, TensorFlow, PyTorch, or similar frameworks
Build scalable APIs for AI inference using FastAPI, Flask, or Node.js
Develop retrieval-augmented generation (RAG) pipelines using Pinecone, Weaviate, FAISS, or vector databases
Implement embeddings, semantic search, and AI-powered workflows
Optimize inference performance, latency, and cost efficiency

Full-Stack Application Development

Build frontend interfaces using React, Next.js, Vue, or modern JavaScript frameworks
Develop backend systems and APIs that connect AI models with business logic
Create user-facing AI features such as chatbots, copilots, dashboards, and automation tools
Ensure applications are responsive, secure, scalable, and production-ready
Build microservices and scalable backend architectures

Data Engineering & Pipelines

Develop ETL pipelines for ingesting, cleaning, transforming, and managing datasets
Automate preprocessing, data labeling, and workflow orchestration using Airflow, Prefect, or Dagster
Manage structured and unstructured datasets in cloud environments
Maintain reliable pipelines for model training, fine-tuning, and evaluation

Infrastructure, DevOps & MLOps

Containerize AI services using Docker and deploy applications using Kubernetes or cloud infrastructure
Build CI/CD pipelines for model deployments and application releases
Monitor model performance, drift, costs, and system reliability
Work with cloud platforms such as AWS, GCP, Azure, Vertex AI, or SageMaker
Improve scalability, uptime, and infrastructure efficiency

Security, Compliance & Reliability

Implement secure API authentication, access control, and rate limiting
Ensure AI systems comply with GDPR, HIPAA, SOC 2, or related compliance requirements
Maintain monitoring, logging, and observability for production systems
Troubleshoot production incidents and optimize system reliability

Collaboration & Product Development

Partner with product and data teams to define AI-powered product features
Translate AI prototypes into scalable production systems
Participate in sprint planning, technical discussions, and architecture decisions
Maintain clear technical documentation and reproducible workflows

What Makes You a Great Fit

You are both a strong software engineer and a hands-on AI builder
You enjoy shipping AI-powered features that solve real-world business problems
You are comfortable moving from prototype to production independently
You think critically about scalability, performance, cost, and usability
You stay current with rapidly evolving AI tools, frameworks, and infrastructure
You communicate clearly and collaborate effectively across technical and non-technical teams

Required Experience & Skills

3+ years of software engineering experience with AI/ML exposure
Strong proficiency in Python and JavaScript/TypeScript
Experience with AI/ML frameworks such as PyTorch or TensorFlow
Experience deploying ML or LLM systems into production environments
Strong frontend experience with React, Next.js, or Vue
Experience building APIs and backend services
Strong SQL skills and experience with cloud data platforms
Familiarity with Docker, CI/CD pipelines, and cloud deployments

Preferred Experience

Experience building AI-powered SaaS platforms or automation products
Experience with LLM fine-tuning, embeddings, and RAG systems
Familiarity with vector databases and semantic search infrastructure
Experience with MLOps tools such as MLflow, Kubeflow, Vertex AI, or SageMaker
Knowledge of microservices, serverless architectures, and distributed systems
Experience optimizing inference cost and performance at scale

What a Typical Day Looks Like

A Full-Stack AI Engineer’s day revolves around building production-ready AI systems and scalable applications. You will:
Build and optimize AI-powered APIs and backend services
Develop frontend interfaces for AI-driven experiences and workflows
Maintain data pipelines and model integration systems
Monitor production environments for performance, uptime, and cost efficiency
Collaborate with engineering and product teams to prioritize and ship AI features
Troubleshoot system bottlenecks and continuously improve scalability and reliability
In short: you help transform AI capabilities into scalable, production-grade products that drive real business impact.
Key Metrics for Success (KPIs)
Successful deployment of AI-powered features on schedule
Application uptime and infrastructure reliability maintained at high standards
Fast and stable inference performance for production endpoints
Reduction in manual workflows through AI automation
Strong adoption and usage of AI-powered product features
Scalable, maintainable, and cost-efficient system architecture

Interview Process

Initial Phone Screen

Video Interview with Pavago Recruiter
Technical Assessment (AI API + Full-Stack Integration Exercise)
Client Interview with Engineering Team
Offer & Onboarding
#AIEngineer #FullStackDeveloper #MachineLearning #LLM #ArtificialIntelligence #Python #React #OpenAI #RAG #MLOps #RemoteJobs #SoftwareEngineering
Originally posted on Himalayas

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About the job

Apply before: Nov 15, 2026
Posted on: Nov 1, 2026
Job type: Full Time
Experience level: Mid-level
Location requirements: Afghanistan Åland Islands Albania Algeria Andorra Angola Anguilla Antarctica Antigua and Barbuda Argentina Armenia Aruba Austria Azerbaijan Bahamas Bahrain
179 more
Barbados Belarus Belgium Belize Benin Bermuda Bolivia Bonaire, Sint Eustatius and Saba Bosnia and Herzegovina Botswana Bouvet Island
Hiring timezones: Worldwide
Job categories: Data Science Developer
Skills: AI Engineer AI Full Stack Developer AI Full Stack Engineer Full Stack AI Developer Full Stack AI Engineer Full Stack AI Engineering Full Stack Developer Full Stack Machine Learning Engineer Machine Learning Engineer Mid Level Full Stack AI Engineer

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Production AI Engineer