Backend Engineer (AI Agentic)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Backend Engineer (AI Agentic) based in Brazil.

   This is a senior backend engineering opportunity focused on building intelligent, autonomous AI systems and scalable backend architectures. You will work at the intersection of Python engineering, LLMs, agentic workflows, and advanced retrieval technologies. The role offers the opportunity to design sophisticated AI agents and multi-agent systems that transform complex data into reliable, goal-oriented solutions. You’ll build production-grade backend services while developing RAG pipelines and vector-based retrieval capabilities. Working alongside product owners, data scientists, and engineers, you’ll turn ambitious AI concepts into robust technical solutions. The environment is collaborative, fast-paced, international, and focused on solving challenging problems at the forefront of applied AI.

Accountabilities:

• Design and implement sophisticated AI agents and multi-agent workflows using frameworks such as LangChain, LangGraph, or Semantic Kernel, ensuring reliable and scalable agent behavior.

• Build, maintain, and optimize high-performance backend services and APIs using Python to support AI-driven applications and features.

• Develop and improve Retrieval-Augmented Generation (RAG) pipelines that provide AI agents with accurate, relevant, and context-aware information.

• Architect and manage vector database solutions such as Pinecone, Weaviate, or similar technologies to enable efficient similarity search and retrieval at scale.

• Integrate Large Language Models with internal APIs, external services, and other systems to expand agent capabilities and deliver complete AI-powered workflows.

• Collaborate closely with product owners, data scientists, and engineering teams to translate complex and evolving AI requirements into production-ready solutions.

• Contribute to technical decisions around architecture, performance, reliability, and scalability while helping establish robust engineering practices for AI systems.

Requirements:

• 6+ years of professional experience with

Python

and its ecosystem, including strong experience building robust backend services and APIs.

• 3+ years of hands-on experience with

LangChain, LangGraph, Semantic Kernel

, or comparable agentic AI frameworks.

• Strong understanding of

agentic AI design patterns

, autonomous workflows, and the practical integration of LLM capabilities into production systems.

• Proven experience developing and optimizing

Retrieval-Augmented Generation (RAG)

solutions and working with vector search technologies such as Pinecone, Weaviate, or similar platforms.

• Strong backend architecture and software engineering skills, with the ability to design scalable, reliable, and maintainable systems.

• Excellent English communication skills, both written and verbal, for technical collaboration, documentation, meetings, and interviews.

• A highly collaborative mindset, with the ability to work effectively across engineering, product, and data teams while navigating ambiguous and rapidly evolving technical challenges.

• Experience with Kubernetes or Docker, advanced prompt engineering, LLM fine-tuning, Pandas or Spark, and LLM monitoring tools such as LangSmith is considered a plus.

Benefits:

• 100% remote full-time contractor opportunity from Brazil.

• Opportunity to work on cutting-edge AI projects involving autonomous agents, LLMs, RAG, and intelligent backend architectures.

• International collaboration with distributed teams and exposure to challenging software engineering and AI use cases.

• Consistent collaboration with teams aligned to Central Time (CT), including key ceremonies, stand-ups, and technical sessions.

• Opportunity to work closely with product owners, data scientists, and experienced engineers in a collaborative environment.

• Exposure to modern AI frameworks, vector databases, cloud infrastructure, and emerging AI engineering practices.

• Daily professional communication and technical collaboration in English.

• How Jobgether works:
  We use an

AI-powered matching process

to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
https://jobgether.com/how-jobgether-works  Why Apply Through Jobgether?   

• Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

 
 
#LI-CL1

• 6+ years of professional experience with

Python

and its ecosystem, including strong experience building robust backend services and APIs.

• 3+ years of hands-on experience with

LangChain, LangGraph, Semantic Kernel

, or comparable agentic AI frameworks.

• Strong understanding of

agentic AI design patterns

, autonomous workflows, and the practical integration of LLM capabilities into production systems.

• Proven experience developing and optimizing

Retrieval-Augmented Generation (RAG)

solutions and working with vector search technologies such as Pinecone, Weaviate, or similar platforms.

• Strong backend architecture and software engineering skills, with the ability to design scalable, reliable, and maintainable systems.
• Excellent English communication skills, both written and verbal, for technical collaboration, documentation, meetings, and interviews.
• A highly collaborative mindset, with the ability to work effectively across engineering, product, and data teams while navigating ambiguous and rapidly evolving technical challenges.
• Experience with Kubernetes or Docker, advanced prompt engineering, LLM fine-tuning, Pandas or Spark, and LLM monitoring tools such as LangSmith is considered a plus.