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.
