Google AI Architect

Google AI Architect/AI and Engineering

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success.

You'll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses.

Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure.

These solutions are powered by engineering for business advantage, transforming mission-critical operations.

We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms.

Our delivery models are tailored to meet each client's unique requirements.

Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise.

We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach.

Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.

Recruiting for this role ends on 10-31-2026

Work you'll do:


* Architect and deliver enterprise AI platforms and applications on Google Cloud using Vertex AI and Gemini; optimize for scalability, reliability, security, and cost.


* Design, fine-tune, evaluate, and govern LLM solutions with Gemini on Vertex AI (prompt/tool/function calling, safety policies, Vector Search, evaluation); implement deployment, inference optimization, and monitoring.


* Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability.


* Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines and Cloud Build.


* Lead cloud-native development on GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL/Spanner, Memorystore, and Terraform; enforce application and agentic design patterns.


* Implement security and governance for AI/ML systems (data privacy, model poisoning, adversarial attacks); apply Gemini safety features and enterprise guardrails.

Responsibilities include:


* Architect and Design: Design and development of enterprise-grade AI applications and platforms, with a focus on scaling AI solutions for production.

This includes defining the technical architecture, selecting appropriate technologies, and ensuring solutions are robust, scalable, and secure.


* LLM and AI Integration: Integrate and fine-tune Large Language Mo...