Full-Stack Engineer

Location: New York, NY; Austin, TX

Department: Engineering

About this Role:

As a Datalinx founding engineer, your goal will be to design, develop, and implement end-to-end data and AI solutions that integrate robust data connectors with intelligent, AI-driven agentic systems and ML-based pattern recognition. Your work will directly support client business outcomes and data flow needs through a secure, scalable, AI-native, and cloud-based data integration solution. You will ensure that the Datalinx product enables business users, data scientists and data engineers to quickly employ use-case-based data flows from source data to target schema, and to activate the data to drive business outcomes.  

Key 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.

Ideal Experience:

• 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.

Datalinx AI is an equal opportunity employer, and we value diversity at our company. We don’t discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

The base salary range for this position is $100,000-$160,000 plus equity and benefits. Datalinx AI offers benefits including health insurance (medical, dental, vision) and paid time off. Final compensation will be determined based on factors including experience, qualifications, and location.

About the Company

Datalinx is an AI Data Refinery that transforms messy consumer data into clean, actionable fuel for AI applications and innovation. The platform combines curated ontologies that reflect business-defined entities, relationships, and logic with agentic workflows to turn messy consumer data into governed, production-ready assets for marketing, advertising, and customer experience use cases. Headquartered in NYC with an engineering hub in Austin, Datalinx enables brands and platforms to operationalize their customer data end-to-end with speed, governance, and scale.

Founded by a seasoned team from Amazon, Oracle, Verizon, Intuit, Unity, and multiple successful startups, Datalinx accelerates time-to-value while improving trust and consistency. It gives business leaders faster access to usable data, insights, and audiences, and frees engineering teams from manual data preparation and ad hoc data requests, enabling seamless, data-driven decisions across the enterprise.