Компания "Lincoln Labs"
About the Role
We are looking for a Full-Stack Software Engineer with a strong foundation in Python and TypeScript to join our engineering team. You’ll play a key role in transforming our legacy BI and reporting platform into a modern, AI-enabled data intelligence system.
You’ll help us integrate AI agents for data cleaning, build a semantic layer that unifies business logic across data sources, and maintain reliable data pipelines that power financial and operational reporting for enterprise clients.
This is a hands-on engineering role with high visibility and the opportunity to work at the intersection of data systems, AI workflows, and modern software engineering.
Key Responsibilities
Refactor and modernize our existing BI platform to support AI integration and SOC 2 compliance.
Collaborate with data, AI, and customer success teams to troubleshoot and resolve customer-facing data/reporting issues.
Design, build, and maintain APIs, services, and UIs that support new agentic workflows and data cleaning capabilities.
Support migration and maintenance of Snowflake, DBT, and related data models.
Develop systems to track, audit, and visualize data transformation history and agent actions.
Apply modern software engineering best practices—testing, CI/CD pipelines, code reviews, and version control.
Work closely with leadership to shape the architecture of AI-assisted data tools and workflows.
Qualifications
4+ years of professional software engineering experience.
Strong skills in Python and TypeScript/React.
Understanding of data systems, ETL/ELT, and tools like Snowflake or DBT.
Familiarity with AI or LLM-based applications is a strong plus.
Experience building reliable, maintainable software using modern development principles (CI/CD, testing, structured workflows).
Ability to navigate ambiguity and help define technical direction in evolving product areas.
Strong communication and collaboration skills across distributed teams.
Must be available to work during Eastern Time Zone business hours.
Preferred Experience
Prior work in analytics, data products, or AI/automation tools.
Experience building semantic layers or metadata-driven systems.
Familiarity with SOC 2 or enterprise compliance frameworks.
Background in both product and infrastructure engineering.
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