Google AI Architect

Google AI Senior Consultant/AI & 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 4/21/2026.

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: Lead the 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 Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an emphasis on production-level performance and reliability.
• Enterprise Architecture: Collaborate with enterprise architects to ensure AI solutions align with the broader company's technical strategy, governance, and standards.
• Cloud and GenAI Native Development: Design and deploy applications using Cloud Native principles on a hyperscaler platform (AWS, Azure, GCP). Leverage a wide range of hyperscaler tools and services, including containers (Docker, Kubernetes), serverless functions, and managed databases. Should have experience in leveraging various GenAI tools to accelerate software development life cycle.
• Security & Governance: Ensure the security of all AI/ML systems by addressing potential vulnerabilities such as data privacy concerns, model poisoning, and adversarial attacks.
• Design Patterns: Apply and enforce Application Design Patterns and Agentic Design Patterns to build resilient and maintainable software systems.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering or a related technical field.
• 5+ years’ experience as a Software or Solution Architect, with a strong focus on application development and scaling solutions for production environments.
• 3+ years hands-on with Google Cloud, including 2+ end-to-end enterprise implementations in production.
• 4+ years designing and implementing Google Cloud networks, security controls, and landing zones using Terraform.
• 3+ years building and operating containerized workloads on GKE (autoscaling, ingress, monitoring/observability).
• 3+ years implementing CI/CD and DevSecOps with Cloud Build, GitHub Actions, or Jenkins.
• 3+ years executing migration or modernization programs to Google Cloud (rehost, replatform, refactor).
• 2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, including 1+ years’ production deployment (e.g. RAG with Vertex AI Search/Vector Search, prompt design, safety policies, observability).
• Deep understanding of AI/ML concepts, including experience with LLMs and their application in enterprise settings.
• Experience implementing multiple AI solutions in a professional, real-world environment.
• Strong understanding of security implications related to AI/ML systems (e.g., data privacy, model poisoning, adversarial attacks).
• Familiarity with various hyperscaler tools and services.
• Hyperscaler Architect certification is required (e.g., AWS Certified Solutions Architect, Azure Solutions Architect Expert, or GCP Professional Cloud Architect).
• Ability to travel up to 50%based on the work you do and the clients and industries/sectors you serve.

Preferred Qualifications:

• Google Professional Machine Learning Engineer certification or the equivalent ML certification.
• Master’s degree in technology-related discipline.
  • 2+ years’s leading high performance, results driven engineering teams delivering AI platforms or applications.
  • 1+ year implementing LLMOps/MLOps using Vertex AI Pipelines and Cloud Build (or similar)

Sponsorship:

• Limited immigration sponsorship may be available.