About Purgo AI
Purgo AI delivers LLM based agentic design, development and deployment of data applications over cloud data warehouses. Purgo AI dramatically improves productivity, reduce costs and shortens time to delivery for data engineering teams.
Purgo AI is based in Palo Alto, CA and funded by The Hive and Capital One Growth Ventures. The company’s co-founder and CTO, Sang Kim, has been an engineering leader across VMWare and Blackberry. Early users of the product include leading enterprises in the life sciences, media and financial services verticals. Purgo AI’s in-built Vertical Solutions have saved users months of time, cost and efforts by getting to production within days. Prominent execs from several cloud data warehouse leaders are advisors to Purgo AI. The product integrates with leading cloud data warehouses including Databricks, Snowflake, and others.
Purgo AI helps automate the building ETL/ELT pipelines and BI applications on cloud data warehouses. The product offers data engineering teams an end-to-end requirements-to-production design, development, test & deployment of ETL/ELT pipelines.
- Purgo AI Vertical Solutions come pre-built with comprehensive Process Definition Libraries written by subject matter experts in natural language as easy-to-edit Jira tickets.
- Business analysts or product owners specify ETL/ELT user requirements as Jira tickets through Purgo AI’s Jira app either by easily editing in-built process definitions or creating new ones.
- This triggers the generation of a design (Behavior-driven design (BDD)) specification. The design creates test harnesses with test scripts and test data for QA.
- Purgo AI then generates source code from integrated code-generation LLMs by using the design specifications without needing any human prompting.
- For enterprise context the product integrates seamlessly with Github and GitLab (to interpret existing/legacy source code and pipelines), and data warehouse catalogs (for schema).
- The generated code is subject to pre-generated quality assurance tests, and test fails re-trigger generation of the source code. The final source code is ready for end deployment over the cloud data warehouse after inspection/approval by the business analyst team.
The entire process has end-to-end traceability through Purgo AI generated log entries across Jira and GitHub systems. Across the end-to-end development process, Purgo AI produces intermediate development artifacts enabling developers transparent, white-box review.
In addition to ETL/ELT pipelines for Business Intelligence applications, in the future Purgo AI will provide a range of requirements-to-production workflows, viz. cloud migration and on-demand machine learning.
About the role
Purgo AI is seeking a Principal AI Engineer to spearhead the development and integration of AI applications and agents using multiple Large Language Models (LLMs). In this role, you will build and optimize AI-driven solutions that advance Purgo AI’s generative AI agent-powered software design lifecycle. This is a hands-on, highly technical position, requiring close collaboration with our product and customer teams to design and implement AI workflows using our AI Applications framework—enabling streamlined management of AI processes and integrations.
Responsibilities
- Develop and Deploy AI Applications: Design and implement AI agentic flow using Python and LangChain to expand Purgo AI’s platform functionality.
- Integrate LLMs: Seamlessly integrate multiple LLMs and APIs into the platform to enhance its generative AI capabilities.
- Design AI Workflows: Build and optimize AI workflows using LangChain to streamline AI process management.
- Collaborate Across Teams: Work closely with product managers, data scientists, and engineering teams to define, design, and deliver platform features.
- Optimize AI Models and Applications: Focus on performance, scalability, and reliability of AI models and their implementations.
- Stay Updated: Continuously research advancements in AI and LLM technologies to drive innovation.
- Troubleshoot and Debug: Address technical challenges in AI applications and ensure seamless integrations.
- Enhance AI Infrastructure: Contribute to improving Purgo AI’s tools, pipelines, and overall infrastructure for AI applications.
- Document Work: Maintain clear documentation of designs, experiments, and implementations to support collaboration and knowledge sharing.
- Enhance AI Infrastructure: Contribute to the continuous improvement of Purgo AI’s AI infrastructure, tools, and pipelines.
- Documentation: Document designs, experiments, and code to facilitate collaboration and knowledge sharing.
About you
- Educational Background: Bachelor’s or higher degree in Computer Science, Engineering, or a related field.
- Experience: At least 8 years of experience in large-scale distributed systems, including a minimum of 2 years focused on Generative AI engineering.
- Programming Expertise: Strong experience with Python, particularly for AI Agent workflows using LangChain, as well as proficiency in Django or FastAPI for web services.
- LLM Integration: Proven ability to integrate multiple LLMs and work with related APIs.
- NLP Knowledge: Solid understanding of natural language processing and related techniques.
- Collaboration Skills: Ability to thrive in a fast-paced, collaborative environment.
- Communication: Strong verbal and written communication skills to convey technical concepts effectively.
Preferred Skills (Bonus):
- Experience with cloud platforms like AWS, Azure, or Google Cloud.
- Knowledge of ETL processes, data warehousing, and data integration techniques.
- Familiarity with behavior-driven development (BDD) and code-generation LLMs.
- Certifications in AI, machine learning, or cloud platforms.
Interested candidates should reach out to sang@purgo.ai.
Purgo AI is an affirmative action employer and welcomes candidates who will contribute to the diversity of the company.
