Full Stack Engineer

BMA Group Global; San Juan (PR); On-site; USD 130,000 - 180,000; Full time

Job summary

BMA Group Global is seeking a hands-on Full-Stack AI Engineer to drive production-ready AI features across backend and frontend. You will implement AI/NLP pipelines, build robust APIs, and integrate LLM capabilities into scalable cloud-native applications.

The role emphasizes API-centric design, containerized deployments with Docker/Kubernetes, and CI/CD automation, collaborating with cross-functional teams to deliver cutting-edge AI solutions.

Qualifications

• 5+ years of experience in full-stack development with Python/Django and React.
• 2+ years of hands-on AI/ML solution development and integration (Generative AI, NLP, LLMs).
• Strong ML fundamentals, NLP, and model integration skills.
• Experience delivering AI-powered features via APIs or microservices.
• Experience building and automating CI/CD pipelines with Jenkins, Git, and Artifactory.

Responsibilities

• Lead backend development with Python/Django and frontend with React.
• Develop, deploy, and maintain production-ready AI/ML features and APIs.
• Integrate Generative AI, LLMs, chatbots, and recommendation systems into apps.
• Work with AI frameworks (LangChain, LangGraph, LlamaIndex, PyTorch, TensorFlow, scikit-learn).
• Integrate AI/LLM APIs (OpenAI, Azure OpenAI, Anthropic, Google Gemini, Hugging Face).
• Build AI-powered apps using vector databases (Pinecone, Qdrant, Milvus, Weaviate, pgvector, Elasticsearch, OpenSearch).
• Design REST APIs and manage PostgreSQL schemas.
• Collaborate across cloud platforms (AWS, Azure, Google Cloud, Oracle Cloud).
• Support cloud marketplace validation, onboarding, publishing, lifecycle automation via APIs/CLI.

Skills

Python

Django

React

APIs

DevOps

Tools

Docker

Kubernetes

Jenkins

Git

Artifactory

LangChain

Job description

Employment Type: Full-time

About the Opportunity

We are seeking an experienced Full-Stack AI Engineer with strong expertise in backend development using Python/Django, frontend development using React, and applied Artificial Intelligence.

The ideal candidate will have hands-on experience developing scalable applications, integrating AI/ML solutions into production environments, and implementing modern DevOps practices, containerization, and CI/CD pipelines.

Key Responsibilities

• Lead backend development using Python and Django, and frontend development using React.
• Develop, deploy, and maintain production-ready AI/ML features, including machine learning models, NLP pipelines, and AI APIs.
• Integrate Generative AI, LLMs, chatbots, and recommendation systems into web and cloud-native applications.
• Work with AI frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face Transformers, PyTorch, TensorFlow, and scikit-learn.
• Integrate AI/LLM APIs from platforms such as OpenAI, Azure OpenAI, Anthropic, Google Gemini, and Hugging Face.
• Build AI-powered applications using vector databases and search technologies such as Pinecone, Qdrant, Milvus, Weaviate, pgvector, Elasticsearch, or OpenSearch.
• Design and develop REST APIs and manage PostgreSQL database schemas.
• Work with cloud platforms including AWS, Azure, Google Cloud, and Oracle Cloud.
• Support cloud marketplace product validation, onboarding, publishing, and lifecycle automation through APIs, CLI tools, and partner integrations.
• Build and automate CI/CD pipelines using Jenkins, Git, and Artifactory.
• Deploy and manage containerized applications using Docker and Kubernetes.
• Collaborate with DevOps, cloud engineering, and data engineering teams.

Required Qualifications

• 5+ years of experience in full-stack software development using Python/Django and React.
• 2+ years of hands-on experience developing and integrating AI/ML solutions, including Generative AI, NLP, LLMs, or machine learning applications.
• Strong understanding of machine learning fundamentals, natural language processing, and algorithm implementation.
• Experience architecting AI-powered features delivered through APIs or microservices.
• Practical experience building and automating CI/CD pipelines using Jenkins, Git, and Artifactory.
• Hands-on experience with Docker and Kubernetes, including deployment, scaling, and automation.
• Familiarity with DevOps practices and infrastructure automation.
• Experience with cloud-based application development and deployment.

Nice to Have

• Certifications in AI/ML, AWS, Azure, or Kubernetes.
• Experience deploying large language models or Generative AI solutions.
• Familiarity with Helm, Terraform, and Infrastructure as Code (IaC).
• Experience with secure AI delivery pipelines, artifact governance, and compliance workflows.

Ideal Candidate Profile

A hands-on software engineer who combines full-stack development, applied AI/LLM engineering, and cloud-native deployment experience.

The ideal candidate can independently develop backend and frontend components, integrate AI capabilities into real-world applications, and contribute to automated, scalable, production-ready software delivery.