Semi Senior AI Engineer
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Job Description
Semi Senior AI Engineer focusing on AI-driven systems and data pipelines. Collaborating with senior engineers on design, development, and implementation of AI solutions in a remote LATAM context.
Responsibilities:
- Contribute to AI web app and 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
- Assist in designing and managing text embeddings and vector stores within Databricks for vector indexing and retrieval solutions
- Support the design, development, and maintenance of custom tools implemented as MCP servers and Databricks applications to enhance agent and model capabilities
- Collaborate in the design, development, and implementation of AI Agents using frameworks like LangChain and LangGraph
- Help implement LLM scorers to validate and monitor agents, applications, and models, while learning to prevent issues like hallucinations or unnecessary actions through structured testing and guardrails
- Participate in continuous improvement efforts through prompt engineering, pipeline optimization, vector store tuning, and scorer refinement to ensure high-quality LLM responses
- Work alongside senior engineers on production deployments, monitoring, and scalability of ML and LLM-based services
Requirements:
- 4-6 years of industry experience in software engineering or related roles
- Strong command of Python, including developing production services, working with asynchronous programming, and writing tests
- Practical experience with AI agent development frameworks such as LangChain, LangGraph, and LlamaIndex
- Experience leveraging 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 implementations
- Experience implementing Retrieval-Augmented Generation (RAG) solutions, including data ingestion, retrieval, and LLM generation
- Experience designing, 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 proficiency, both written and verbal.
Benefits:
- Health insurance
- Flexible work arrangements
- Professional development opportunities
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