Related skills
rag langchain llamaindex langgraph vector databases📋 Description
- Lead reference architecture for AI and agentic systems in key product domains.
- Design and deliver production-grade AI systems with reliability, scalability, observability, and cost efficiency.
- Establish platform-level AI/data components, including model broker, multi-model routing, telemetry, and cost governance tooling.
- Lead end-to-end AI data pipelines: ingestion, OCR, NER, embeddings, vector stores, and hybrid search.
- Partner with data/analytics and product teams to align AI solutions with measurable outcomes.
- Mentor engineers and drive adoption of shared AI/data practices across teams.
🎯 Requirements
- Proven experience leading and delivering production AI systems across multiple engineering teams.
- Strong background in AI engineering with a data-first mindset; large-scale data pipelines and analytics-driven evaluation.
- Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex, or equivalents.
- Deep understanding of RAG and agentic architectures, including embeddings, vector databases, evaluation harnesses, and cost/latency tradeoffs.
- Experience designing or contributing to offline and online evaluation methodologies tied to product metrics.
- Experience implementing security by design and responsible AI in regulated or enterprise SaaS environments.
🎁 Benefits
- Benefits starting from Day 1
- Retirement Plan Matching
- Flexible Paid Time Off
- Wellness Support Programs and Resources
- Parental & Caregiver Leaves
- Fertility & Adoption Support
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