Job Summary:
Quinn AI is seeking a highly skilled Senior Full Stack Developer with deep experience in data engineering, third-party integrations, and machine learning (ML) data pipelines. The ideal candidate will have a strong background in both front-end (React) and back-end development, coupled with expertise in building and maintaining data pipelines for ML applications and integrating with external systems such as SFDC, HubSpot, and NetSuite. This role requires strong leadership and the ability to manage complex, scalable software solutions in a cloud-based environment.
Quinn AI is an innovative early-stage startup founded by two former Amazon executives. We have achieved promising early results and aim to revolutionize traditional business and revenue operations. By integrating a best-in-class 'Revenue Operating System' with advanced machine learning analytics and a conversational AI advisor, we are poised to disrupt the industry.
Key Responsibilities:
Full Stack Development:
- Design and develop scalable full-stack applications using Python frameworks (Django/Flask) for the back-end and React for the front-end.
- Build and maintain responsive, user-friendly front-end interfaces using React and modern JavaScript (ES6+).
- Develop RESTful APIs for seamless communication between the front-end and back-end services.
Data Engineering and ML Pipelines:
- Lead the design and development of data pipelines for ML applications, ensuring seamless integration of data sources, transformations, and model outputs.
- Develop and optimize ETL (Extract, Transform, Load) pipelines for processing large volumes of data from third-party systems such as SFDC, HubSpot and NetSuite.
- Collaborate with Data Scientists and ML engineers to ensure data pipelines efficiently support ML model training, deployment, and inference.
- Implement data cleaning, validation, and transformation processes to ensure high-quality data flow to ML models.
Machine Learning Integration:
- Work with data scientists to integrate ML models into production environments, ensuring that models are correctly deployed and utilized by applications.
- Optimize ML workflows to leverage real-time data processing for predictive analytics and decision-making.
Cloud Services and Infrastructure:
- Architect and manage applications in cloud environments (AWS preferred), leveraging services such as Lambda, S3, API Gateway, and RDS.
- Design and implement serverless architectures to ensure scalability, high availability, and cost efficiency.
- Implement CI/CD pipelines for automated testing, deployment, and monitoring, ensuring fast, reliable software delivery.
Database & API Integration:
- Design and manage relational databases (PostgreSQL) for storing and processing application and integrated third-party data.
- Develop and manage API integrations with external systems like HubSpot, Lightspeed, and NetSuite to ensure smooth data flow between platforms.
- Ensure the security, performance, and scalability of database and API services.
Version Control and Collaboration:
- Use Bitbucket and GitHub for version control and collaborative development.
- Participate in code reviews, testing, and debugging processes.
Technical Leadership and Mentorship:
- Stay updated with the latest trends and advancements in full-stack development, ML, and LLM technologies.
Qualifications:
Education:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
Technical Skills:
- Full Stack Development: Expertise in Python (Django/Flask) and React for building robust web applications.
- Data Engineering: Strong experience with data pipelines, ETL processes, and integrating third-party systems (HubSpot, Lightspeed, NetSuite).
- Machine Learning: Hands-on experience in integrating and deploying ML models in production, ensuring efficient data flow through pipelines.
- Cloud Infrastructure: Deep experience with AWS services (Lambda, S3, API Gateway, RDS) for deploying and managing scalable cloud applications.
- DevOps: Knowledge of CI/CD pipelines, automated testing, and cloud infrastructure management.
- Database Management: Expertise in PostgreSQL and experience managing large datasets with optimized queries.
- Front-End Development: Proficiency in React, JavaScript, HTML, and CSS for building dynamic, responsive front-end applications.
- API Development: Experience building and consuming RESTful APIs to integrate external services.
Professional Experience:
- 5+ years of experience as a Full Stack Developer with significant involvement in data engineering and ML pipeline integration.
- Proven ability to integrate third-party systems into robust, scalable applications.
- Experience working with cloud infrastructure, managing data pipelines, and optimizing ML workflows.
- Experience leading and mentoring development teams, managing end-to-end project delivery.
- Familiarity with containerization tools like Docker and orchestration platforms.
Soft Skills:
- Excellent communication and teamwork abilities.
- Strong analytical and organizational skills.
- Ability to mentor and guide junior team members.
Application Process:
Interested candidates are invited to submit resumes and a cover letter detailing their relevant experience and why they are a good fit for this role.