Senior AI/ML Engineer – Agentic AI & LLMs

BMA Group Global; San Juan (PR); On-site; USD 140,000 - 190,000; Full time

Job summary

BMA Group Global in the United States/ Puerto Rico region seeks an experienced AI/ML professional specializing in Agentic AI and Generative AI to design, develop, and deploy production-ready AI solutions. You will build AI agents, LLM-powered applications, RAG pipelines, and scalable cloud-native systems, collaborating with cross-functional teams to deliver enterprise-grade AI.

This role requires strong Python skills, experience with LangGraph/LangChain, Kubernetes, Docker, and a solid

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
• 4–7 years of experience developing production ML/AI systems.
• Minimum 1 year of hands-on experience with Generative AI and LLM applications.
• Strong Python programming experience.
• Experience with Agentic AI frameworks such as LangGraph, LangChain, or equivalent.
• Knowledge of RAG, vector databases, LLM APIs, and prompt engineering.
• Experience with MCP, function calling, or AI agent orchestration.
• Familiarity with Kubernetes, Docker, CI/CD, and backend APIs.
• Strong machine learning and statistical analysis foundations.

Responsibilities

• Design, develop, and deploy Agentic AI workflows using LangGraph, LangChain, or similar frameworks.
• Build AI agents with multi-step reasoning, tool calling, and MCP integrations.
• Develop RAG pipelines, vector search, and LLM-powered applications.
• Build production-grade AI/ML solutions using Python.
• Implement AI evaluation, testing, observability, and performance optimization.
• Deploy containerized AI services using Kubernetes, Docker, and CI/CD pipelines.
• Collaborate with cross-functional engineering teams to deliver scalable AI solutions.

Skills

Python programming

Generative AI

LLM applications

Machine learning

Education

Bachelor's degree in Computer Science or related field

Tools

LangGraph

LangChain

Kubernetes

Docker

CI/CD

Vector databases

Job description

We are partnering with a leading global technology company seeking an experienced AI/ML professional specializing in Agentic AI and Generative AI to develop and deploy intelligent, production-ready AI solutions.

This opportunity focuses on building advanced AI agents, LLM-powered applications, and scalable cloud-native systems to support complex enterprise operations.

Key Responsibilities

• Design, develop, and deploy Agentic AI workflows using LangGraph, LangChain, or similar frameworks.
• Build AI agents with multi-step reasoning, tool calling, and MCP integrations.
• Develop RAG pipelines, vector search, and LLM-powered applications.
• Build production-grade AI/ML solutions using Python.
• Implement AI evaluation, testing, observability, and performance optimization.
• Deploy containerized AI services using Kubernetes, Docker, and CI/CD pipelines.
• Collaborate with cross-functional engineering teams to deliver scalable AI solutions.

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
• 4–7 years of experience developing production ML/AI systems.
• Minimum 1 year of hands-on experience with Generative AI and LLM applications.
• Strong Python programming experience.
• Experience with Agentic AI frameworks such as LangGraph, LangChain, or equivalent.
• Knowledge of RAG, vector databases, LLM APIs, and prompt engineering.
• Experience with MCP, function calling, or AI agent orchestration.
• Familiarity with Kubernetes, Docker, CI/CD, and backend APIs.
• Strong machine learning and statistical analysis foundations.

Preferred Qualifications

• Experience with AWS Bedrock, OpenSearch, or similar cloud AI services.
• Experience with AI agent evaluation and observability.
• Knowledge of networking systems or troubleshooting applications.

Why Consider This Opportunity?

Join an innovative technology environment working on next-generation Agentic AI solutions, with opportunities to contribute to enterprise-scale AI products and collaborate with highly specialized engineering teams.