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Datalinx AI

Senior Full-Stack Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 10 years of combined full-stack development experience, with specialization in machine learning, data engineering, and knowledge of agentic application design.
  • Strong proficiency in Python, Golang, and SQL, with hands-on experience using PostgreSQL.
  • Expertise building integrations with Databricks, including REST APIs and Delta Lake operations, and Snowflake, including connectors, Snowpark, and query optimization.
  • Experience with data engineering tools such as dbt.
  • Proficiency with large language models and hands-on experience with AI agent frameworks such as LangGraph or AutoGen.
  • Proficiency with machine learning libraries such as scikit-learn and expertise in unsupervised and supervised machine learning techniques for pattern recognition.
  • Experience with enterprise data workflows involving unstructured and structured datasets.
  • Knowledge of data pipeline orchestration tools such as Apache Airflow, Dagster, or dbt.
  • Familiarity with data governance, security, and best practices in cloud environments.
  • Ability to work independently and collaboratively.

Responsibilities

  • Design, develop, and maintain secure, scalable implementations of the product.
  • Build AI-driven agentic solutions using frameworks such as LangGraph and design prompt engineering strategies for reliable agent performance.
  • Integrate AI agents with client data systems such as Databricks and Snowflake for intelligent querying and data retrieval.
  • Develop tools that automate domain-specific machine learning model training processes, including clustering, churn prediction, personalization, and anomaly detection, to improve customer business outcomes.
  • Ensure secure authentication, authorization, and data governance compliance across data integration and AI solutions.
  • Implement observability, monitoring, and continuous improvement for data pipelines and AI agent workflows.
  • Collaborate with client teams and other engineering disciplines to support customer business outcomes.
  • Document deployment and usage best practices to assist customers.

About the Company

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