AI Engineer (AWS Bedrock / Agentic AI / Python / Golang)

Location: Remote (LATAM)

Employment Type: Contract (Long-Term)

About the Role

We are looking for a highly skilled AI Engineer to design and develop next-generation Generative AI applications using the AWS AI ecosystem. You will build intelligent AI agents, evaluation frameworks, and scalable backend services that power enterprise-grade AI solutions.

This role is adecuado for engineers who enjoy working with LLMs, AI Agents, Retrieval-Augmented Generation (RAG), prompt engineering, and AI evaluation while building production-ready applications.

Responsibilities

Design, develop, and deploy Generative AI applications using Amazon Bedrock.

Build intelligent AI agents using AWS AgentCore and AWS Strands.

Develop scalable backend APIs and microservices using Python and Go (Golang).

Build Retrieval-Augmented Generation (RAG) pipelines.

Design prompt engineering and prompt optimization strategies.

Develop AI evaluation frameworks including:

LLM-as-a-Judge

Human-in-the-Loop evaluation

Prompt evaluation

Model benchmarking

Implement automated testing and quality assurance for AI applications.

Work with vector databases and embedding models.

Collaborate with product managers, architects, and engineering teams to deliver enterprise AI solutions.

Optimize AI applications for performance, reliability, scalability, and cost.

Required Qualifications

5+ years of software engineering experience.

Strong Python development experience.

Experience with Go (Golang).





Hands-on experience with Amazon Bedrock.

Experience building Generative AI applications using LLMs.

Experience with AI Agents and agentic workflows.

Experience developing REST APIs and backend services.

Strong understanding of prompt engineering.

Experience with Git and CI/CD.

Preferred Qualifications

Experience with one or more of the following:

AWS AgentCore

AWS Strands

LangChain

LangGraph

MCP (Model Context Protocol)

Vector databases (OpenSearch, Pinecone, Weaviate, Chroma, FAISS)

Knowledge graphs

AI evaluation tools such as:

DeepEval

Ragas

Promptfoo

TruLens

LangSmith

LLM-as-a-Judge methodologies

Human evaluation and calibration frameworks

Prompt evaluation and benchmarking

AWS Lambda

ECS/EKS

Docker

Kubernetes

Terraform

Nice to Have

AI testing and quality engineering experience.

Experience building AI copilots or AI assistants.

Experience with observability and monitoring for AI applications.

Experience working with enterprise-scale cloud environments.

Technologies

Amazon Bedrock

AWS AgentCore

AWS Strands

Python

Go (Golang)

LangChain

LangGraph

MCP

Vector Databases

Docker

Kubernetes

REST APIs

Git

CI/CD

What You'll Work On

You will be part of a team building enterprise AI solutions that leverage Large Language Models, intelligent AI agents, retrieval systems, and advanced evaluation frameworks to deliver secure, scalable, and production-ready AI applications for enterprise customers.

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