Pavago

Pavago

Pavago specializes in connecting small and medium-sized businesses with skilled offshore talent from Pakistan and Latin America, offering a streamlined recruitment process that enables the hiring, onboarding, and payment of remote employees at signific...

IT Services
Founded 2023

Description

  • Design, build, and deploy end-to-end AI-powered applications for production use.
  • Integrate LLMs and machine learning models into scalable application environments.
  • Develop AI features such as chatbots, semantic search, document intelligence, copilots, and workflow automation.
  • Build scalable APIs and backend services that expose AI capabilities to applications.
  • Create Retrieval-Augmented Generation (RAG) pipelines and implement vector-database-based semantic search.
  • Build and maintain ETL pipelines for structured and unstructured data, including ingestion, cleaning, validation, and versioning.
  • Develop modern front-end interfaces and ensure applications are responsive, secure, and production-ready.
  • Deploy applications and models using Docker, Kubernetes, and CI/CD pipelines.
  • Monitor model performance, inference latency, infrastructure reliability, and cloud cost efficiency.
  • Collaborate with product managers, data scientists, and engineering teams to deliver AI features and document systems.

Requirements

  • 3+ years of software engineering experience with exposure to AI/ML systems.
  • Experience building production AI applications and deploying machine learning models into production environments.
  • Strong proficiency in Python and JavaScript/TypeScript.
  • Hands-on experience with OpenAI APIs, Hugging Face, PyTorch, and TensorFlow.
  • Experience building scalable REST APIs.
  • Front-end development experience with React, Next.js, or Vue.js.
  • Strong SQL skills and experience working with cloud databases.
  • Experience using Docker, Kubernetes, and CI/CD pipelines.
  • Familiarity with vector databases and AI inference services.
  • Nice to have: experience building AI-powered SaaS platforms, working with embeddings, fine-tuning, and RAG, or using MLflow, Kubeflow, Vertex AI, or SageMaker.
  • Nice to have: familiarity with serverless architectures, microservices, AI observability, evaluation frameworks, and model drift monitoring.
  • Must be available to work U.S. client business hours with flexibility for sprint planning, deployments, and experimentation cycles.

Benefits

  • Full-time, remote work arrangement.
  • Opportunity for end-to-end ownership of production AI applications.
  • Exposure to modern LLMs, RAG pipelines, MLOps, and cloud technologies.
  • Collaborative engineering culture with significant technical ownership.
  • Clear progression into senior technical and leadership roles.
  • Long-term career growth opportunity.
  • Interview process includes a Spark Hire intro video that can be recorded at your convenience.

Interested in this position?

Apply directly on the company website

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