Senior AI Engineer
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Job Description
Senior AI Engineer focusing on building and improving AI-driven systems. Collaborating on data pipelines and AI solutions in a remote LATAM environment.
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.
Requirements:
- 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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