Gen AI Engineer

We are looking for a Gen AI Engineer to collaborate with a US-based client!

We seek an AI and AI Agent Developer/Engineer to design, develop, and deploy advanced AI agents that enhance enterprise automation, decision-making, and intelligent data processing. This role requires strong Python expertise, proficiency in AI agent orchestration frameworks (LangGraph, AutoGen, CrewAI), and hands-on experience with multi-modal models, retrieval-augmented generation (RAG/GraphRAG), and machine learning integrations. The ideal candidate is passionate about AI-driven automation, knowledge graphs, graph databases, and ontologies.

Key Reponsibilities

AI Agent Development & Orchestration – Build AI-powered agents for multi-agent collaboration, autonomous decision-making, and long-running workflows using LangGraph, AutoGen, CrewAI, etc.

Large Language Models (LLMs) & Multi-Modal AI – Work with LLMs (GPT-4, Claude, LLaMA, Mistral), fine-tune models, integrate multi-modal AI (text, image, video, speech), and implement RAG/GraphRAG for knowledge extraction.

API Development & Cloud Integration – Develop AI-powered APIs (FastAPI, Flask, gRPC), deploy models on cloud platforms (GCP, AWS, Azure), and implement MLOps pipelines for automated model lifecycle management.

Knowledge Graphs & Graph Databases – Develop AI agents that interact with knowledge graphs (Neo4j, TigerGraph, Amazon Neptune) for reasoning and retrieval, leveraging ontologies and semantic search.

Collaboration & Agile Development – Work in Agile teams, track progress in Jira, participate in code reviews, and contribute to sprint planning.

Required Skills & Experience

• +4 Years of experience as a Software Engineer (MUST HAVE)
• Proficiency in Python, with experience in AI/ML frameworks like TensorFlow, PyTorch, Hugging Face, and OpenAI APIs.
• GCP Vertex experience
• Experience developing AI agents using LangGraph, AutoGen, CrewAI, or similar agent frameworks.
• Expertise in retrieval-augmented generation (RAG) and GraphRAG for knowledge-based AI applications.
• Hands-on experience with LLM integration in production environments, including fine-tuning and prompt engineering.
• API development experience, including FastAPI, Flask, GraphQL, and gRPC.
• Cloud AI experience, prioritizing open-source, followed by GCP, AWS, and Azure.
• Strong experience in knowledge graphs and graph databases such as Neo4j, ArangoDB, Amazon Neptune.

Preferred Qualifications

• Experience in AI Ethics & Responsible AI development, ensuring fairness and bias mitigation in AI models.
• Understanding of reinforcement learning (RLHF, PPO, or SAC) for training AI agents.
• Expertise in scalable AI deployment, using Ray, Dask, or Spark for distributed AI processing.
• Experience with MLOps and model versioning using Kubeflow, MLflow, or Airflow.
• Knowledge of distributed AI architectures (e.g., multi-agent RL, federated learning).
• Contributions to open-source AI projects or research publications in AI agent-based systems.

Why Join Us?

• Full-time position
• 100% remote anywhere in LATAM
• Payment in USdollars
• 12 PTO per year
• Holidays from your country off and paid
• Birthday off and paid
• Career Path
• Recognition Program
• Paid Leaves