Sr AI Engineer – Generative AI & Agentic Systems

We’re looking for an exceptional SrAI Engineer to join our growing Data & AI practice and help build the next generation of AI-powered solutions.

This role is ideal for someone who loves working at the edge of what’s possible with LLMs, RAG, agents, semantic search, multimodal AI, and intelligent automation — and who wants to turn cutting-edge ideas into real, production-ready systems for clients across industries.

This position is open to candidates based in LATAM or the United States.

What You’ll Do

• Design, build, and deploy advanced AI solutions using LLMs, RAG, embeddings, vector databases, semantic search, and agentic architectures.
• Develop intelligent systems that can process documents, retrieve knowledge, generate content, automate workflows, and transform unstructured data into actionable insights.
• Work with modern GenAI and AI engineering tools such as LangChain, LangGraph, Hugging Face, PyTorch, MCP, multi-agent frameworks, and cloud-native AI services.
• Build scalable, reliable AI applications across Azure, AWS, Databricks, or similar cloud/data platforms.
• Experiment with and evaluate foundation models, prompts, retrieval strategies, orchestration patterns, and performance optimization techniques.
• Collaborate closely with engineering, product, data, and business teams to define the right technical approach and deliver high-impact AI solutions.
• Stay plugged into the fast-moving GenAI ecosystem and bring new ideas, tools, and prototypes into real-world applications.

What You Bring

• Strong experience in AI, machine learning, data science, or AI engineering, with hands-on exposure to production-scale solutions.
• Deep interest and practical experience with Generative AI, including LLMs, RAG, vector search, embeddings, agents, and AI workflow orchestration.
• Strong Python skills and experience with modern ML/AI frameworks and libraries.
• Experience building on cloud or data platforms such as Azure, AWS, GCP, Databricks, or similar.
• A solid foundation in data science, experimentation, statistical thinking, or applied machine learning.
• Ability to work with structured and unstructured data, including text, documents, images, emails, spreadsheets, or other complex data formats.