Zipdev is helping its client in building and evolving software that supports modern clinical and operational workflows. The product surface includes Windows desktop applications and connected services, with a strong emphasis on reliability, maintainability, and customer experience. As a Full‑Stack Engineer, you will deliver end-to-end capabilities across the Windows client, service/business logic layers, and the database. Your primary stack will include C++ (MFC) for desktop UI and application behavior, C# for services and shared business logic, and MS SQL for data persistence. Key Responsibilities Full‑Stack Delivery (End‑to‑End) - Design, build, and maintain features across the full stack (C++/MFC desktop → C# services/business logic → MS SQL). - Own features from requirements through implementation, test readiness, release, and production support. - Collaborate with QA and product partners to refine acceptance criteria, validate behavior, and ensure release readiness in an Agile cadence. - Participate in AI-augmented development workflows, reviewing and validating AI-generated code against acceptance criteria. - Follow Git best practices: feature branches, pull requests for all changes, and clear commit hygiene; proactively update documentation when behavior or architecture changes. Desktop (C++ / MFC) - Design, build, and maintain Windows workflows using C++ and MFC. - Debug and remediate defects across UI, threading, memory/resource management, and performance hotspots. - Modernize and refactor legacy areas to improve maintainability, testability, and stability while preserving user workflows. - Implement defensive coding patterns and robust error handling suitable for regulated environments. Services & Business Logic (C#) - Develop and maintain C# components and service layers that support desktop workflows and integrations. - Design and consume APIs or internal contracts as needed to connect client and service components. - Implement secure authentication/authorization patterns appropriate for enterprise and regulated contexts. - Create and maintain automated checks and diagnostics to support supportability and observability. Data Layer (MS SQL) - Design and evolve MS SQL schemas with emphasis on clarity, performance, and data integrity. - Write and optimize queries, stored procedures, and migration scripts where appropriate. - Collaborate with QA and Engineering to validate data correctness and enable reliable test data setup. - Contribute to troubleshooting production issues through data analysis and root cause investigation. Quality, Testing, and Agile Execution - Demonstrate knowledge of QA processes in an Agile environment, including acceptance criteria, defect triage, regression awareness, and collaboration with QA roles. - Contribute to test strategy (unit/integration as appropriate), and ensure features meet functional, security, and reliability expectations. - Maintain a disciplined approach to compliance and secure engineering practices.

Role Description Zipdev is helping its client in building and evolving software that supports modern clinical and operational workflows. The product surface includes Windows desktop applications and connected services, with a strong emphasis on reliability, maintainability, and customer experience. As a Full‑Stack Engineer, you will deliver end-to-end capabilities across the Windows client, service/business logic layers, and the database. Your primary stack will include: - C++ (MFC) for desktop UI and application behavior - C# for services and shared business logic - MS SQL for data persistence Qualifications - Strong experience developing Windows desktop applications using C++ and MFC - Strong experience developing with C# (services, libraries, or application layers) - Solid relational database skills with MS SQL (schema design, query awareness, performance basics) - Proven ability to debug complex issues across layers (UI ↔ business logic ↔ database) and drive fixes to completion - Familiarity with Git-based workflows (pull requests, code reviews) and maintaining engineering documentation - Hands-on experience using AI coding assistants as part of daily development, with a clear understanding of the Human → AI → Human review loop and human accountability - Strong understanding that Protected Health Information (PHI) must never appear in code, logs, tests, commits, or error messages; comfort working with synthetic/mock data - Awareness of secure coding practices (no hardcoded credentials, least-privilege access patterns, safe error handling) - Must be located in LATAM and have high English proficiency (C1+) Requirements - Design, build, and maintain features across the full stack (C++/MFC desktop → C# services/business logic → MS SQL) - Own features from requirements through implementation, test readiness, release, and production support - Collaborate with QA and product partners to refine acceptance criteria, validate behavior, and ensure release readiness in an Agile cadence - Participate in AI-augmented development workflows, reviewing and validating AI-generated code against acceptance criteria - Follow Git best practices: feature branches, pull requests for all changes, and clear commit hygiene; proactively update documentation when behavior or architecture changes - Design, build, and maintain Windows workflows using C++ and MFC - Debug and remediate defects across UI, threading, memory/resource management, and performance hotspots - Modernize and refactor legacy areas to improve maintainability, testability, and stability while preserving user workflows - Implement defensive coding patterns and robust error handling suitable for regulated environments - Develop and maintain C# components and service layers that support desktop workflows and integrations - Design and consume APIs or internal contracts as needed to connect client and service components - Implement secure authentication/authorization patterns appropriate for enterprise and regulated contexts - Create and maintain automated checks and diagnostics to support supportability and observability - Design and evolve MS SQL schemas with emphasis on clarity, performance, and data integrity - Write and optimize queries, stored procedures, and migration scripts where appropriate - Collaborate with QA and Engineering to validate data correctness and enable reliable test data setup - Contribute to troubleshooting production issues through data analysis and root cause investigation - Demonstrate knowledge of QA processes in an Agile environment, including acceptance criteria, defect triage, regression awareness, and collaboration with QA roles - Contribute to test strategy (unit/integration as appropriate), and ensure features meet functional, security, and reliability expectations - Maintain a disciplined approach to compliance and secure engineering practices Benefits - Work remotely Monday - Friday, 40 hours a week (no weekends) - Health Care Reimbursement - Active Lifestyle Reimbursement - Quarterly Home Office Reimbursement - Did we mention it's REMOTE?!!

• Developing and maintaining services for control plane including API endpoints, configuration management, and platform workflows • Building customer-facing features that enable users to configure, manage, and interact with inference platform resources • Writing well-tested, well-documented code and participating in code reviews to maintain engineering standards • Collaborating with engineering and product teams to translate requirements into reliable platform capabilities • Contributing to platform reliability through monitoring, debugging, and operational support of control plane services

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