About Aviato Consulting
Aviato Consulting is an elite, ex-Googlers-founded GCP solutions firm and consecutive Best Place to Work winner. Combining an innovative, Google-style engineering culture with zero bureaucracy, we offer true remote freedom from anywhere in India, full ESOP access after six months, and the opportunity to tackle high-impact challenges alongside the elite minds of the ecosystem.
We are seeking a Senior Full Stack AI Engineer to design, deploy, and scale machine learning models and AI-driven applications primarily on Google Cloud Platform (with some Azure exposure). In this role, you will bridge the gap between heavy-duty data engineering and interactive product design. You will build high-performance backend AI infrastructure, establish scalable ML pipelines, and integrate them into fluid, user-facing applications driven by advanced agentic engineering.
LLMOps & Model Deployment: Train, test, scale, and optimize machine learning models within Google Cloud Vertex AI. Implement semantic search and memory infrastructure using vector databases (Vertex AI Vector Search, Pinecone, ChromaDB, or pgvector).
Dual-Ecosystem Backend Engineering: Build robust, low-latency backend systems, asynchronous event loops, and middleware routers using Python (FastAPI or Django) and JavaScript/TypeScript (Node.js) optimized specifically for agentic data flows and RESTful APIs.
Cloud Data Architecture: Process, organize, and structure massive datasets utilizing Google Cloud BigQuery. Design real-time stream and scheduled batch pipelines via GCP Cloud Dataflow and Apache Beam to support continuous model training.
Adaptive Frontend Architecture: Stitch together complex, responsive web interfaces and AI-generated component modules using React, Next.js, and Tailwind CSS, ensuring interfaces are highly capable of handling Server-Sent Events (SSE) for real-time token streaming.
AI-Native Workflows: Orchestrate codebase context within next-gen AI environments (e.g., Claude Code, AntiGravity) by designing system-context directories (skills.md, architecture.md) to drive deterministic, compilable code generation.
Infrastructure Optimization: Architect and optimize full-stack ML infrastructure for high performance, low latency, and maximum cost efficiency on GCP.
Education: Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
Experience: 8+ years of professional software engineering experience, with a proven track record of shipping production-grade full-stack features.
Programming Mastery: Strong, concurrent programming proficiency across both Python and JavaScript/TypeScript ecosystems.
Cloud & Data Foundational Skills: Solid experience with Google Cloud Platform (GCP), managing relational/NoSQL databases, processing structured datasets, and implementing runtime data validation schemas.
Application Delivery: Experience designing, optimizing, and consuming complex, high-performance RESTful APIs tailored for real-time event distribution within cross-functional engineering teams.
Production AI/ML Engineering: Extensive hands-on experience engineering, evaluating, and scaling machine learning models and autonomous, agentic solutions within live production environments.
Advanced Google Cloud Expertise: Deep technical expertise across GCP serverless compute functions, Vertex AI architectures, and complex BigQuery workflows.
Enterprise DevOps & Multi-Cloud: Solid understanding of multi-cloud infrastructure environments (GCP/Azure), comprehensive version control systems (Git), and configuring containerized CI/CD pipelines.
100% Remote Freedom: Work from anywhere in India.
True Ownership: Full ESOP access after just six months.
Elite Culture: Google-caliber engineering standards with zero corporate bureaucracy.