What You Will Do
Architect & Build: Design and implement end-to-end GenAI applications using Python, LangChain, and LlamaIndex on Google Cloud
Engineer for Precision: Develop advanced RAG (Retrieval-Augmented Generation) pipelines and Semantic Search systems using Google Cloud Vector Search or Pinecone
Optimize Models: Lead efforts in LLM and Embedding fine-tuning to improve domain-specific performance
Agentic Ops: Build and manage agentic workflows that automate complex multi-step reasoning tasks
Collaborate & Innovate: Work directly with customers to understand requirements, suggest novel features, and implement state-of-the-art AI techniques
- Productionize: Apply MLOps best practices to ensure models are served efficiently, monitored, and continuously improved
- Your Technical Toolkit:
- Core Languages: Mastery of Python and shell scripting
AI/LLM Ecosystem: Extensive experience with Google Gemini, GPT-4, or LLaMA; deep knowledge of Prompt Engineering and Fine-tuning
Data & Search: Expertise in Vector Databases (Vertex AI Vector Search, pgvector, etc.) and implementing Semantic Search
Infrastructure: Hands-on experience with Google Cloud (Vertex AI) and building scalable software architectures
Frameworks: Proficiency in LangChain, LlamaIndex, or similar orchestration layers
- Mindset: A strong software engineering foundation—you write clean, maintainable code and understand the full SDLC
- Basic Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
5+ years of experience in AI/ML
Proven track record of deploying GenAI products to a production environment
Experience with Classic Machine Learning (neural nets, training, tuning) is a strong plus
- Knowledge of Data Engineering and SQL
- Personal Attributes:
- Ownership: You take pride in your code and see projects through from concept to deployment
Curiosity: The AI landscape changes weekly; you are a lifelong learner who stays ahead of the curve
Consultative Spirit: You enjoy interacting with clients and can translate technical complexity into business value
Ethics: You prioritize responsible AI development and data privacy
