Job Description

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 ( >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

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