Software Engineer

Position Overview
We’re looking for full-time Software Engineers and AI Systems / ML Engineers to join our growing startup team as one of the first hires. We are hiring front-end, back-end, full-stack and AI Systems / ML engineers (and full-stack engineers). In this hands-on role, you’ll play a critical part in shaping the look and feel and/or data infrastructure that powers our platform. You’ll work closely with the CTO, CEO, COO, and other key team members to design and build scalable data pipelines and web scraping systems and/or dynamic front-end visualizations.

Front-End Engineer (Back-End and AI Systems / ML descriptions are further down)

As one of our first front-end hires, you’ll work closely with the CTO, CEO, and other key team members to translate insights into intuitive, accessible visuals. You will be responsible for both the design and front-end development of our platform, making your mark on everything from user research to the deployment of front-end code.

We’re looking for someone with a passion for development and a visual eye, who is excited to learn, grow, and make an impact at an early stage of a rapidly growing company.

Key Responsibilities

Front-End Development (60%)

• Translate designs into functional, production-ready code using HTML, CSS, JavaScript, and frameworks like Svelte.
  
   
• Work closely with other developers to integrate UI components with back-end systems.
  
   
• Optimize websites for performance, SEO, and scalability.
  
   
• Contribute to the overall front-end ecosystem, bringing your knowledge of modern front-end technologies to the team.
  
   

UI/UX Design (30%)

• Create wireframes, prototypes, and high-fidelity mockups using tools like Figma, Adobe XD, or Sketch.
  
   
• Design responsive interfaces optimized for cross-device compatibility and accessibility standards.
  
   
• Maintain and evolve design systems to ensure consistency across all products.

User Research & Strategy (5%)

• Participate in user research activities like interviews, surveys, and usability testing to identify pain points and inform design decisions.
  
   
• Collaborate with the team on analyzing competitor products and market trends to help shape design strategy.
  
   
• Help develop personas, user flows, and journey maps to ensure designs are aligned with user needs and business goals.
  
   

Collaboration & Teamwork (5%)

• Present design concepts to team members, receiving and incorporating feedback to refine designs.
  
   
• Work closely with product managers, engineers, and marketers to ensure design and development efforts are aligned with project goals and timelines.
  
   
• Engage in team discussions and brainstorming sessions, sharing your insights and contributing to process improvements.
  
   

Required Skills

• Design Tools: Proficiency in Figma, Adobe XD, Sketch, or similar design tools.
  
   
• Front-End Tech: Strong knowledge of HTML, CSS, JavaScript, and experience with frameworks like Svelte.
  
   
• Research Methods: Familiarity with usability testing, card sorting, and analytics tools.
  
   

Preferred Qualifications

• 0–1 years of experience in UI/UX design or front-end development exposure (internships or personal projects are great).
  
   
• Familiarity with CMS platforms (e.g., WordPress) and graphics tools is a bonus.
  
   
• Experience with Tailwind and Svelte is a plus.
  
   
• Degree in Computer Science, or a related field (or equivalent experience).

Back-End Engineer:

As one of the first back-end engineers, you’ll have a unique opportunity to define and implement the back-end architecture for our platform. Your work will directly impact the way we collect, store, and process data, setting the foundation for future growth. This is a great opportunity to grow your skills while contributing to high-visibility projects in a fast-paced, collaborative environment.

Key Responsibilities
Data Architecture & Engineering (60%)

• Design and implement cloud-native data pipelines (AWS/GCP/Azure) using modern ETL/ELT frameworks.
  
   
• Architect storage solutions for scraped datasets, such as data lakes and data warehouses.
  
   
• Develop API integrations for third-party data sources and internal systems.
  
   
• Implement data quality monitoring and governance frameworks to ensure the accuracy and reliability of data.
  
   

Web Scraping & Acquisition (30%)

• Build high-performance scraping systems using Python, Scrapy, and Selenium.
  
   
• Solve challenges related to dynamic content (JavaScript-heavy sites, CAPTCHAs).
  
   
• Ensure compliance with regulations like robots.txt, GDPR, and other data privacy standards.
  
   
• Optimize proxy rotation and anti-blocking mechanisms for efficient and reliable scraping.
  
   

Collaboration & Learning (10%)

• Participate in code reviews, learning from senior engineers and contributing to team best practices.
  
   
• Work closely with data scientists and other engineers to understand requirements and create technical solutions.
  
   
• Help coordinate sprint planning and contribute to technical problem-solving within the team.
  
   

Preferred Qualifications

• Proficiency with the Python data stack (Pandas, Scrapy, SQLAlchemy).
  
   
• Experience designing cloud data solutions using AWS, GCP, or Azure (e.g., AWS Redshift, GCP BigQuery).
  
   
• Strong experience with large-scale web scraping operations (handling 10M+ records).
  
   
• Knowledge of distributed systems (Spark, Kafka, Airflow).
  
   
• Experience with browser automation tools (Playwright, Selenium).
  
   
• Understanding of data privacy standards and compliance (GDPR, CCPA).
  
   
• Experience with building ML data pipelines is a plus.
  
   
• Cloud/data engineering certifications (AWS, Google Cloud) are a bonus.
  
   
• Degree in Computer Science, Data Engineering, or related field (or equivalent experience).
  
   
  
   

AI Systems & ML Engineer:

As one of the first Systems & ML engineers, you’ll have the opportunity to round out the skillset of the team. The experience you get from working at an early stage startup in this capacity, where you'll be the person people turn to for AI Systems / ML questions, will accelerate your career trajectory and knowledge. 

AI Systems & ML Infrastructure (50%)

• Design, implement, and optimize infrastructure for training, fine-tuning, and deploying machine learning models at scale (e.g., LLMs, embedding models, classifiers).
  
   
• Build scalable, low-latency inference systems and APIs for integrating models into production.
  
   
• Develop and manage experiment tracking, model versioning, and evaluation pipelines using tools like MLflow, Weights & Biases, or custom setups.
  
   
• Collaborate with data scientists to operationalize research into robust engineering solutions.
  
   
• Ensure reliability and observability of AI systems in production, including monitoring, logging, and performance optimization.
  
   

Data Engineering & Platform (30%)

• Architect and implement cloud-native data pipelines (AWS/GCP/Azure) using modern ETL/ELT frameworks.
  
   
• Build data ingestion pipelines from third-party APIs and internal systems.
  
   
• Design data storage systems to support model training and downstream analytics (e.g., data lakes, feature stores, warehouses).
  
   
• Implement data validation, lineage tracking, and quality monitoring.
  
   

Web Scraping & Data Acquisition (10%)

• Maintain and enhance high-throughput scraping systems (Python, Scrapy, Playwright/Selenium).
  
   
• Solve challenges related to dynamic sites, CAPTCHAs, and large-scale acquisition (10M+ records).
  
   
• Ensure compliance with robots.txt, GDPR, CCPA, and data ethics guidelines.
  
   

Team Collaboration & Technical Leadership (10%)

• Work closely with other ML engineers and backend engineers to co-design end-to-end systems.
  
   
• Participate in code reviews, sprint planning, and architecture discussions.
  
   
• Contribute to evolving team best practices in ML engineering and AI system design.
  
   

Preferred Qualifications

• Strong experience deploying and managing ML models in production (batch and real-time inference).
  
   
• Proficiency in Python and the broader data/ML stack (e.g., Pandas, NumPy, SQLAlchemy, Scikit-learn, PyTorch, Hugging Face, etc.).
  
   
• Experience with MLOps tools (MLflow, Airflow, Kubeflow, SageMaker, Vertex AI, or equivalents).
  
   
• Deep understanding of cloud data architecture and services (e.g., AWS S3, Lambda, ECS, Step Functions, GCP BigQuery).
  
   
• Familiarity with web scraping at scale and data ingestion best practices.
  
   
• Solid knowledge of distributed systems and orchestration tools (e.g., Spark, Kafka, Ray).
  
   
• Awareness of AI safety, privacy standards (e.g., GDPR, CCPA), and ethical considerations.
  
   
• Degree in Computer Science, ML/AI, or a related field — or equivalent practical experience.
  
   

Bonus Points For

• Experience with LLM fine-tuning or retrieval-augmented generation (RAG) pipelines.
  
   
• Building internal tooling for model explainability, observability, or performance monitoring.
  
   
• Contributions to open-source AI or data engineering projects.
  
   
• Certifications in cloud platforms (AWS/GCP/Azure) or ML specializations.
  
   

Why Join Us?
Build, publish and nurture AI systems with Santai (www.sant.ai). We will let people build and share their army of AI agents for themselves and their communities. As part of our early-stage team, you’ll be one of the first engineers:

• Impact: Contribute to high-visibility projects in AI, helping us build a platform that will make a real difference in people's lives.
  
   
• Growth: As one of the first hires, you’ll have a unique opportunity to shape the technical direction of the company and grow your skill set in a collaborative, fast-paced environment.
  
   
• Culture: Be part of a flexible, dynamic team where your contributions are valued, and your growth is supported.
  
   
• Benefits: Competitive compensation and benefits package, including company and office perks.