Datalinx Ai

Job Summary:
Datalinx AI is an AI Data Refinery that transforms messy consumer data into actionable insights for AI applications. As a Full-Stack Engineer, you will design, develop, and implement end-to-end data and AI solutions, ensuring the Datalinx product supports client business outcomes with secure and scalable integration.
Responsibilities:
• Design, develop, and maintain secure, scalable implementation of the Datalinx product.
• Build AI-driven agentic solutions using frameworks like LangGraph and/or Autogen, designing effective prompt engineering strategies for reliable agent performance.
• Integrate AI agents with client data systems (Databricks, Snowflake) for intelligent query and data retrieval.
• Develop tools that automate domain-specific ML model training processes (clustering, churn prediction, personalization, anomaly detection) to help create lift for our customer’s business.
• Ensure secure authentication, authorization, and data governance compliance across all data integration and AI solutions.
• Implement observability, monitoring, and continuous improvement for data pipelines and AI agent workflows.
• Collaborate closely with client teams and other engineering disciplines to enable business success for customers.
• Document best practices for deployment and usage of Datalinx to assist customers.
Qualifications:
Required:
• 5-8+ years of combined experience in full-stack development 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 in building integrations to Databricks (REST APIs, Delta Lake operations) and Snowflake (connectors, Snowpark, query optimization).
• Experience with popular data engineering tools like dbt.
• Proficiency with LLMs and hands-on experience with AI agent frameworks (e.g., LangGraph, Autogen).
• Proficiency with machine learning libraries such as Scikit-learn, and expertise in unsupervised/supervised ML techniques for pattern recognition.
• Experience with enterprise data workflows, including handling both unstructured and structured datasets.
• Knowledge of data pipeline orchestration tools (e.g., Apache Airflow, Dagster, dbt).
• Familiarity with data governance, security, and best practices in cloud environments.
• Strong problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment.
Company:
Datalinx AI provides a platform that cleans, transforms, enriches, and monitors data to enable accurate AI insights and automated workflows. Founded in 2025, the company is headquartered in New York, USA, with a team of 2-10 employees. The company is currently Early Stage.