Senior Generative AI Solutions Architect

Are you passionate about Generative AI and Cloud Architecture? We’re looking for a hybrid professional who can turn a blueprint into a fully functional Google Cloud Platform (GCP) solution in under 4 weeks.

What You’ll Do

• Architecture & Design: Build scalable solutions using Vertex AI, BigQuery, and serverless services for millions of requests.
• AI Agent Development: Implement RAG systems with embeddings, vector stores, and Gemini, integrating structured and unstructured data.
• Document Processing: Design pipelines with Document AI and fine-tuned LLMs to extract and analyze complex documents.
• Cost Optimization: Achieve latency <100ms and cost <$0.001/request using Cloud Run, GPUs, and optimized functions.
• Enterprise Integration: Connect APIs (CRM, ERP) via Apigee, Pub/Sub, and Dataflow for event-driven architectures.

Must-Have Technical Expertise

• Generative AI & MLOps:

  • Hands-on with Vertex AI (Fine-tuning, Prompt Management, Model Registry).
  • RAG implementation, embeddings, and relevance evaluation (recall@k >85%).
  • Advanced Gemini API usage and cost optimization.
  • LLM evaluation frameworks (RAGAS, LangSmith).

• Data Engineering at Scale:

  • BigQuery ML, Dataflow (Apache Beam), Pub/Sub with 99.9% SLA.

• Cloud Native Architecture:

  • GKE, Cloud Run, Apigee with advanced security and scalability practices.

• Specialized AI:

  • Document AI, Vision AI, Speech-to-Text with adapted models.

Experience Required

• 3+ Generative AI solutions in production (>1000 active users, <5% error rate).
• At least 2 projects such as:
  • Enterprise chatbot integrated with 3+ systems.
  • Legal/financial document processing pipeline (>95% accuracy).
  • Real-time recommendation engine (>10M events/day).

Nice-to-Have Skills

• Fine-tuning with LoRA/QLoRA.
• Safety & Guardrails (Llama Guard, Content Moderation API).
• Federated Learning and multimodal generation (Imagen 3, Veo, Chirp).

Critical Soft Skills

• Business Translator: Turn “I want a chatbot” into clear technical requirements.
• Velocity: Prototype in 3 days, MVP in 2 weeks, production in 4 weeks.
• Documentation: Communicate trade-offs (latency vs cost, accuracy vs speed).
• Security: Knowledge of GDPR, PII detection, and model governance.

Ready for the challenge? If you meet the requirements and want to lead cutting-edge Generative AI projects at scale, apply now!