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 scalable AI architectures for customer use cases in line with enterprise and security standards • Lead implementation of AI software components such as model serving, orchestration, retrieval, and integrations • Run time-bound proofs of value to demonstrate business outcomes quickly and clearly • Help migrate AI workloads between cloud, on-premises, and hybrid environments on Dell infrastructure • Enable customer engineers and platform teams to support and extend solutions after handover • Design, configure, and implement AI solution stacks, including model serving, orchestration, retrieval pipelines, vector stores, and related components • Select practical tools and patterns to avoid tooling sprawl and deliver working prototypes and PoVs tied to clear success measures • Lead PoV sprints (typically a few weeks): refine scope, build and iterate on solutions, and present outcomes and recommendations to stakeholders • Plan and execute cloud-to-on-prem and hybrid migration patterns for AI workloads onto Dell infrastructure, optimizing performance, reliability, and security • Take shared responsibility for production readiness and early production stability, including monitoring, performance optimization, and issue triage • Work closely with AI Data Specialists to define and consume AI-ready data pipelines that support performance and reliability • Collaborate with AI Strategists and Enterprise Architects to align technical scope with business outcomes and target-state architectures • Provide documentation, runbooks, and knowledge transfer to customer teams, and contribute to Dell AI Factory reference architectures and playbooks • Mentor other technical team members on AI architecture patterns, Dell AI infrastructure capabilities, and responsible AI practices

• Design end-to-end AI systems: combining LLMs, embeddings, retrieval pipelines, and structured outputs into reliable product features. • Build grounding and retrieval layers: indexing docs, OpenAPI specs, and customer data to support accurate, context-aware generation. • Define evaluation systems: measuring accuracy, latency, cost, and user impact; building feedback loops to continuously improve quality. • Handle real-world complexity: malformed specs, inconsistent docs, edge-case APIs, and ambiguous user queries. • Make architectural tradeoffs: latency vs. quality, cost vs. coverage, deterministic vs. generative approaches. • Own production reliability: observability, fallbacks, rate limiting, and safe degradation when systems fail. • Work across the stack: from model orchestration and backend systems to the UI surfaces that expose them.

This is a part-time position. The AoPS Academy Virtual Campus is an after-school and weekend enrichment option for students, most of our Year-Round courses are offered late afternoons to evenings Monday through Friday. Many of our weekday classes start as early as 4pm ET and as late as 10pm ET. Classes are also offered all day on Sundays from 10am ET- 9pm ET. Summer camps are held Mon-Fri between June and August and run for 1, 2, or 4 weeks for 1.5 or 3 hours per day. This might be a good fit if you: - Are a rock-star teacher with a passion for working with high-achieving students - Are an engaging, enthusiastic instructor who can motivate gifted learners - Have strong math content knowledge - Aren’t afraid of student-led instruction, discussions, and allowing students to do the heavy lifting - Foster a classroom environment that encourages critical thinking and problem solving - Are comfortable teaching in a live virtual classroom environment - Have an interest in teaching elementary, middle school and high school levels For each lesson you will: - Teach enthusiastic elementary, middle, and high school students in our online classrooms. - Use our curriculum to teach participation-oriented classes that focus on instruction and developing skills, not on rote memorization. - Work in small classes (average size 12) with top performing students who are passionate about learning and are motivated to succeed. Requirements: - Must have a solid academic background in mathematics. - A bachelor's degree in a STEM field is required. A master's degree or higher in a STEM field is preferred. - Must have some experience using Zoom or similar video conferencing software and be comfortable managing a classroom in a virtual setting. - Must have some experience teaching or tutoring students at the K-12 level. Some experience working with advanced students is preferred. - All functions of this role must be completed in the U.S. Benefits and Compensation: The instructor rate at the Virtual Campus is $30/hour for Year-Round classes. The class rates represent flexible work time, 15 minutes early arrival immediately before class, and actual class time. - Paid Sick Leave * - 401K retirement plan - Eligible for discretionary bonus after 2 years - Employee discount on classes and Beast Academy Online (BAO) yearly subscriptions *Not applicable to all states At this time we are only hiring instructors who are located in and authorized to work in the United States. We are unable to offer sponsorship, including STEM-OPT and H-1B. AoPS Academy is a program of Art of Problem Solving (AoPS), a global leader in K–12 advanced education. AoPS is on a mission to discover, inspire, and train the great problem solvers of the next generation. Since 2003, AoPS has trained hundreds of thousands of the country’s top students through its online school, in-person academies, textbooks, and online learning systems. AoPS Academy offers unique problem solving curriculum at its in-person locations across the country as well as through the virtual campus. Just like our traditional AoPS Academy experience, our range of math course offerings at the AoPS Academy Virtual Campus allows students the opportunity to explore new interests while strengthening their math and problem-solving skills.