GCP AI Architect (Remote)

Job Summary

Core Generative AI & ML Expertise

Strong understanding of Generative AI models (LLMs, multimodal models, embeddings).

Hands-on experience with foundation models (e.g., GPT-style, Claude-style, LLaMA-style) and model adaptation techniques.

Expertise in prompt engineering , prompt orchestration , and agent-based frameworks .

Solid grounding in machine learning fundamentals , including supervised/unsupervised learning, evaluation metrics, and inference optimization.

AI Architecture & System Design

Ability to design scalable, modular GenAI architectures for production use.

Experience with

RAG (Retrieval-Augmented Generation) architectures

Vector databases (semantic search, embeddings indexing)

Multi-agent systems and workflow orchestration

Strong understanding of low-latency inference , model routing , and fallback strategies .

Knowledge of event-driven , microservices , and API-first architectures .

Product Engineering & Integration

Experience integrating GenAI capabilities into customer-facing and internal products .

Ability to translate product requirements into AI-driven capabilities and technical designs.

Familiarity with A/B testing , feature flags, and iterative product releases involving AI.

Data & Knowledge Engineering

Proficiency in data pipelines , feature engineering , and unstructured data processing .

Experience with

Knowledge graphs

Metadata-driven architectures

Document ingestion and chunking strategies

Strong understanding of data quality, provenance, and governance for AI systems.

Cloud, MLOps & Platform Skills

Strong experience in cloud-native environments (GCP).

Familiarity with MLOps practices , including

Model versioning

Deployment pipelines

Monitoring, logging, and drift detection

Experience with containerization , Kubernetes , and CI/CD pipelines.

Knowledge of inference o