05/05/2026
๐ Weโre Hiring: ๐๐ซ. ๐๐ & ๐๐ ๐๐ง๐ ๐ข๐ง๐๐๐ซ
Individual Contributor ยท Full-Time ยท Hybrid
๐๐๐จ๐ฎ๐ญ ๐ญ๐ก๐ ๐๐จ๐ฅ๐
We are looking for a Sr. AI Engineer to design and build production-grade agentic AI systems end-to-end. This is a deeply technical, hands-on role owning architecture, development, deployment, and operations of complex AI systems. You will work on real-world agentic pipelines, RAG systems, and LLM-driven architectures with strong focus on reliability, scalability, and system design from first principles.
๐๐๐ฒ ๐๐๐ฌ๐ฉ๐จ๐ง๐ฌ๐ข๐๐ข๐ฅ๐ข๐ญ๐ข๐๐ฌ
๐น Agentic System Design
โ Architect multi-agent systems with structured context flows, memory strategies, tool-use patterns
โ Design deterministic, observable orchestration layers (LangGraph or custom)
๐น Context Engineering
โ Own prompt architecture, context window management, and RAG pipelines
โ Optimize retrieval systems (hybrid search, re-ranking, chunking)
๐น MCP & Tool Integration
โ Build MCP servers and external tool integrations
โ Design tool-call schemas, fallback strategies, error recovery
๐น Full-Cycle Engineering
โ Build backend services, agent runtimes, APIs, data pipelines
โ Own deployment, monitoring, observability (traces, evals, latency), incident response
๐น Technical Leadership
โ Drive architecture decisions, design reviews, engineering standards
โ Work with product & engineering to translate requirements into scalable systems
๐๐๐ช๐ฎ๐ข๐ซ๐๐ ๐๐ค๐ข๐ฅ๐ฅ๐ฌ & ๐๐ฎ๐๐ฅ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง๐ฌ
โ Bachelorโs/Masterโs in CS, Engineering, or equivalent
โ Daily use of AI tools (Claude Code, Cursor, etc.)
๐นCore: Python (async, typing, performance), Rust (plus)
๐นAgentic AI & LLM Systems: LangChain, LlamaIndex, LangGraph, MCP, context engineering, RAG (Pinecone/Weaviate/pgvector), agent evals, observability (LangFuse/LangSmith)
๐นMachine Learning: Full ML lifecycle (EDA โ deployment), metrics (F1, AUC-ROC), PyTorch, Scikit-learn, XGBoost, HuggingFace, validation (leakage, drift, A/B testing)
๐นBackend & Infra: FastAPI, async systems, streaming, retries, rate limiting, AWS/Azure, Docker
๐นData & Systems: PostgreSQL/pgvector, Redis, MongoDB, Kafka
๐๐ซ๐จ๐๐ฎ๐๐ญ๐ข๐จ๐ง ๐๐ฑ๐ฉ๐๐ซ๐ข๐๐ง๐๐
โ Shipped agentic AI systems in production (not prototypes)
โ Fixed latency, cost, and reliability issues in LLM systems
โ Built regression evaluation frameworks
๐๐ซ๐๐๐๐ซ๐ซ๐๐ ๐๐ฎ๐๐ฅ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง๐ฌ
โ Long-context models, LoRA/QLoRA, distillation
โ Multi-modal agents
โ Rust for performance systems
โ Open-source/research work
โ Startup/high-growth experience
โ ๏ธ ๐ซThis Is Not a People Management Role
๐
๐จ๐๐ฎ๐ฌ:
โ System design
โ Architecture
โ Technical depth
โ Engineering ex*****on
๐
๐๐๐๐๐ฅ๐ข๐ง๐: ๐๐๐ญ๐ก ๐๐๐ฒ ๐๐๐๐
๐ก Apply at ๐ก๐ซ@๐ข๐ง๐๐ข๐ง๐ข๐ญ๐ข๐๐ข๐ญ.๐๐จ๐ฆ with the Subject: โ๐๐ซ. ๐๐ & ๐๐ ๐๐ง๐ ๐ข๐ง๐๐๐ซ โ ๐๐ฑ๐ฉ๐๐๐ญ๐ข๐ง๐ (๐ฑ) ๐๐๐ โ (๐ฑ) ๐ฒ๐ซ๐ฌ ๐๐ฑ๐ฉ๐๐ซ๐ข๐๐ง๐๐ โ (๐ฑ) ๐๐๐ฒ๐ฌ ๐ง๐จ๐ญ๐ข๐๐โ