Fullstack AI Engineer

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.

Key Responsibilities

• 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.

Minimum Qualifications

• 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.

Preferred Qualifications

• 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.

What We Offer

• 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.