Lead AI Engineer
1 мес. назад
159.3k–230k USD / yearLeadRemote
google cloudsalesforcegenerative airag pipelines
Lead AI Engineer responsible for full lifecycle of AI features including document intelligence and RAG pipelines, focusing on scalability, latency, error handling, and cost optimization.
О компании
- About : is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results. If this describes you, we want you on our team. Want to learn more about life at ? Check out these resources in addition to the job des
Обязанности
- 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
Требования
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
- 8+ 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
Другое
- 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
- 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