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Full-Stack AI Engineer

1 month ago
Kenya, South Africa
Full-time
Mid Level
AI Engineer
Software Development
Apache Airflow CI/CD Dagster Datadog Docker FastAPI Flask GCP HIPAA Hugging Face JavaScript Kubeflow Kubernetes Microservices MLflow MLOps Next.js Node.js Prefect Prometheus Python PyTorch React SageMaker Serverless Snowflake SQL TensorFlow TypeScript Vertex AI Vue.js
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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
View All Jobs 521

Description

  • Deploy and integrate pre-trained and fine-tuned ML and LLM models into production environments.
  • Build scalable inference APIs and back-end services that connect AI models to business logic.
  • Implement vector search and retrieval systems and design Retrieval-Augmented Generation (RAG) pipelines.
  • Build ETL pipelines to ingest, clean, transform, and process structured and unstructured data.
  • Automate data preprocessing, labeling, validation, and versioning workflows.
  • Manage datasets and pipelines using orchestration tools and cloud data warehouses.
  • Develop front-end interfaces for AI-powered features such as chatbots, dashboards, search, and analytics tools.
  • Containerize services and deploy workloads to Kubernetes environments.
  • Build and maintain CI/CD pipelines for application and model deployments.
  • Monitor production systems for performance, uptime, latency, observability, security, and cost efficiency.

Requirements

  • 3+ years of software engineering experience with exposure to AI/ML systems.
  • Strong proficiency in Python and JavaScript/TypeScript.
  • Hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, or OpenAI APIs.
  • Experience building scalable APIs and back-end systems.
  • Front-end development experience using React, Next.js, Vue, or similar frameworks.
  • Experience deploying machine learning models into production systems.
  • Strong SQL skills and experience with cloud data warehouses.
  • Familiarity with Docker, Kubernetes, and CI/CD workflows.
  • Experience integrating APIs, vector databases, and AI inference services.
  • Experience building and scaling AI-powered SaaS applications, preferred.
  • Hands-on experience with embeddings, fine-tuning, and RAG pipelines, preferred.
  • Familiarity with MLOps platforms such as MLflow, Kubeflow, Vertex AI, or SageMaker, preferred.
  • Experience with serverless architectures and microservices, preferred.
  • Knowledge of prompt engineering and AI workflow optimization, preferred.
  • Experience optimizing inference latency and AI infrastructure costs, preferred.
  • Familiarity with monitoring model drift, evaluation metrics, and AI observability practices, preferred.

Benefits

  • Full-time remote position.
  • Working hours aligned with U.S. client business hours with flexibility for deployments, experimentation cycles, and sprint schedules.
  • Opportunity to own AI systems end-to-end, from infrastructure and APIs to front-end experiences and deployment pipelines.
  • Work on production AI applications with direct business impact.
  • Collaborate closely with product, engineering, and data teams.
  • Interview process includes a technical assessment and client engineering interviews.

Interested in this position?

Apply directly on the company website

Apply Now

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