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EA22 - Senior AI Engineer at Rockcruit

Roles & Responsibilities

  • 5-8 years of industry experience in software engineering or related roles
  • Strong proficiency in Python, including production services, asynchronous programming, and testing
  • Hands-on experience with AI Agents Development frameworks such as LangChain, LangGraph and LlamaIndex
  • Experience using MLflow for prompt engineering, experimentation, evaluation, model registry, and deployments

Requirements:

  • Build and maintain AI-powered data pipelines and extraction processes (batch and streaming) from internal relational data sources and unstructured documents (PDF, Word, PowerPoint) into structured datasets within Databricks
  • Own end-to-end delivery of AI solutions, from design through production
  • Design and manage text embeddings and vector stores within Databricks for use with vector indexing and retrieval solutions
  • Drive architecture and best practices for AI-powered systems, including developing and maintaining custom tools and facilitating scalable ML/LLM deployments

Job description

Position: AI Engineer Senior

📍LATAM

📌Remote

As a Software Engineer, Artificial Intelligence, you will play a key role in building, operating, and continuously improving AI-driven systems that support internal business capabilities. You will focus on designing and maintaining AI-powered data pipelines, agent-based solutions, and LLM-driven services, working closely with modern data and ML platforms.

This role requires strong software engineering foundations combined with hands-on experience in large language models, vector stores, and ML lifecycle management. You will contribute to scalable, production-grade AI solutions while driving quality, reliability, and continuous improvement across the full model and data pipeline lifecycle.

Responsibilities

  • Build and maintain AI-powered data pipelines and extraction processes (batch and streaming) from internal relational data sources and unstructured documents (PDF, Word, PowerPoint) into structured datasets within Databricks.
  • Own end-to-end delivery of AI solutions, from design through production.
  • Design and manage text embeddings and vector stores within Databricks for use with vector indexing and retrieval solutions.
  • Drive architecture and best practices for AI-powered systems
  • Design, develop, and maintain custom tools implemented as MCP servers and Databricks applications to extend agent and model capabilities.
  • Design, develop and implement AI Agents using frameworks like LangChain and LangGraph.
  • Implement LLM scorers to validate and monitor agents, applications and models. Prevent issues like hallucinations or unnecessary actions through structured testing and guardrails.
  • Drive continuous improvement through prompt engineering, pipeline optimization, vector store tuning, and scorer refinement to ensure high-quality LLM responses.
  • Collaborate on production deployments, monitoring, and scalability of ML and LLM-based services.

Experience & Qualifications

  • 5-8 years of industry experience in software engineering or related roles.
  • Strong proficiency in Python, including production services, asynchronous programming, and testing.
  • Hands-on experience with AI Agents Development frameworks such as LangChain, LangGraph and LlamaIndex.
  • Experience using MLflow for prompt engineering, experimentation, evaluation, model registry, and deployments.
  • Solid understanding of vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma or similar), including serverless or managed options.
  • Experience implementing Retrieval augmented generation (RAG) solutions. Data Ingestion and Retrieval, LLM Generation.
  • Experience building and consuming REST APIs, model serving solutions, and CI/CD pipelines.
  • Experience working with cloud platforms (AWS), containerization (Docker), and modern deployment practices.
  • Hands-on experience with Databricks, Apache Spark, and Delta Lake (nice to have)
  • Advanced English level, both written and verbal.

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