Job Title: Full-Stack AI Engineer Position Type: Full-Time, Remote Working Hours: U.S. client business hours (with flexibility for model deployments, experimentation cycles, and sprint schedules) About the Role: Our client is seeking a Full-Stack AI Engineer to design, build, and deploy AI-powered applications. This role requires bridging software engineering with applied machine learning, ensuring that models are integrated into production systems that are scalable, reliable, and user-friendly. The Full-Stack AI Engineer combines back-end services, front-end interfaces, and machine learning pipelines to deliver practical, business-driven AI solutions. Responsibilities: AI Model Integration: - Deploy pre-trained and fine-tuned ML/LLM models (OpenAI, Hugging Face, TensorFlow, PyTorch). - Wrap models in APIs (FastAPI, Flask, Node.js) for scalable inference. - Implement vector search integrations (Pinecone, Weaviate, FAISS) for retrieval-augmented generation (RAG). Data Engineering & Pipelines: - Build ETL pipelines for ingesting, cleaning, and transforming text, image, or structured data. - Automate data labeling, preprocessing, and versioning with Airflow, Prefect, or Dagster. - Store and manage datasets in cloud warehouses (Snowflake, BigQuery, Redshift). Application Development (Full-Stack): - Build front-end UIs in React, Next.js, or Vue to surface AI-powered features (chatbots, dashboards, analytics). - Design back-end services and microservices to connect models to business logic. - Ensure responsive, intuitive, and secure interfaces for end users. Infrastructure & Deployment: - Containerize ML services with Docker and deploy to Kubernetes clusters. - Automate CI/CD pipelines for model updates and application releases. - Monitor latency, cost, and model drift with MLflow, Weights & Biases, or custom dashboards. Security & Compliance: - Ensure AI systems comply with data privacy standards (GDPR, HIPAA, SOC 2). - Implement rate limiting, access control, and secure API endpoints. Collaboration & Iteration: - Work with data scientists to productionize prototypes. - Partner with product teams to scope AI features aligned with business needs. - Document systems for reproducibility and knowledge transfer. What Makes You a Perfect Fit: - Strong coder with a foundation in both full-stack development and applied ML/AI. - Comfortable building prototypes and scaling them to production-grade systems. - Analytical problem solver who balances performance, cost, and usability. - Curious and adaptable, staying current with emerging AI/LLM tools and frameworks. Required Experience & Skills (Minimum): - 3+ years in software engineering with exposure to AI/ML. - Proficiency in Python (PyTorch, TensorFlow) and JavaScript/TypeScript (React, Node.js). - Experience deploying ML models into production systems. - Strong SQL and experience with cloud data warehouses. Ideal Experience & Skills: - Built and scaled AI-powered SaaS products. - Experience with LLM fine-tuning, embeddings, and RAG pipelines. - Knowledge of MLOps practices (Kubeflow, MLflow, Vertex AI, SageMaker). - Familiarity with microservices, serverless architectures, and cost-optimized inference. What Does a Typical Day Look Like? A Full-Stack AI Engineer’s day revolves around connecting models to real-world applications. You will: - Review and refine model APIs, testing latency and accuracy. - Write front-end code to surface AI features in user-friendly interfaces. - Maintain pipelines that clean and prepare new datasets for training or fine-tuning. - Deploy updates through CI/CD pipelines, monitoring cost and performance post-release. - Collaborate with product and data science teams to prioritize AI features that solve real user problems. - Document workflows and results so solutions are repeatable and scalable. In essence: you ensure AI moves from prototype to production — reliable, compliant, and impactful. Key Metrics for Success (KPIs): - Successful deployment of AI features to production on schedule. - Application uptime ≥ 99.9% and inference latency < 500ms for key endpoints. - Reduction in manual workflows replaced by AI features. - Model performance tracked and stable (accuracy, drift, false positives/negatives). - Positive user adoption and satisfaction of AI-driven features. Interview Process: - Initial Phone Screen - Video Interview with Pavago Recruiter - Technical Assessment (e.g., deploy a small ML model with API endpoints and basic front-end integration) - Client Interview(s) with Engineering Team - Offer & Background Verification

• Design and implement insights and analytics dashboards for the CTV self-service platform, providing users with actionable data to enhance their campaigns. • Develop both frontend (70%) and backend (30%) services using React, Next.js, and TypeScript, ensuring seamless integration between components. • Build robust, scalable APIs using tRPC to serve analytics data to the frontend application. • Create efficient pages using server-side rendering (SSR) or static site generation (SSG) via Next.js for performance-optimized analytics displays. • Collaborate with designers to implement responsive and visually appealing user interfaces using Tailwind CSS, ensuring a smooth, intuitive experience for the platform’s users. • Optimize the full stack to ensure quick load times, low-latency data fetching, and smooth user experiences, especially for data-heavy visualizations and analytics pages. • Deploy and manage the platform using Vercel, taking advantage of its serverless functions for backend processes and ensuring efficient deployments and scaling. • Participate in code reviews, pair programming, and knowledge-sharing sessions to ensure high-quality, maintainable code. • Implement unit and end-to-end testing for both frontend and backend components to ensure reliability and reduce bugs in production.

• Lead and execute product development initiatives from prototype to user adoption, in collaboration with product and design and your peers in engineering • Participate in technical architecture discussions and help the team make key technical decisions. • Solve difficult technical problems throughout the software stack and get projects over the finish line, across front-end, back-end, or infrastructure. • Proactively identify and address opportunities for enhancement—be it in code quality, user experience, or overall performance—and lead initiatives to make these improvements happen.

• Join a team that is focused on delighting our customers and partners, executing the organization's mission, and propelling our business forward. • Build products utilizing Next.js / React, TypeScript, Ruby on Rails, GraphQL and test libraries such as Jest and Chromatic. • Proactively manage the infrastructure and platform dependencies to ensure the existing application remains robust, secure, and scalable. • Respond to corporate client and business needs by evolving existing products and identifying high-impact areas for new initiatives. • Partner with our data technology team to transform complex data models into intuitive, user-facing features that simplify the ordering experience. • Decompose complex problems into elegant technical designs and collaborate with fellow engineers to implement, test, and validate your team’s output. • Communicate clearly with your team to maintain mission alignment and provide technical guidance on complex projects. • Continually improve the user experience by increasing system efficiency based on research, user data, and performance metrics. • Actively contribute ideas to improve our product, tech stack, and internal development workflows. • Embrace new challenges in a fast-paced environment and contribute to every stage of the development lifecycle as we scale our services. • Have fun creating meaningful, sustainable software alongside a talented and supportive team!