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Eureka Labs logo
Eureka Labs

Excelling Product Factory Partner for fast-growing marketplaces & SaaS companies. #ThinkBuildEnjoy #ChallengeYourself

AI Engineer

AI EngineerMachine Learning EngineerFull TimeRemoteSeniorTeam 51-200Since 2017H1B No SponsorCompany SiteLinkedIn

Location

Argentina

Posted

108 days ago

Salary

0

Seniority

Senior

Job Description

AI Engineer

Eureka Labs

• 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. • Design and manage text embeddings and vector stores within Databricks for use with vector indexing and retrieval solutions. • 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.

Job Requirements

  • 4-6 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.
  • Advanced English level, both written and verbal.
  • Hands-on experience with Databricks, Apache Spark, and Delta Lake (nice to have).

Benefits

  • N/A

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