Staff AI Engineer

Responsibilities:

• Design and deploy cutting-edge AI agents using our orchestration layer built on n8n, Temporal, and next-gen agentic stacks.
• Build intelligent, context-aware workflows that plug directly into enterprise systems — transforming how businesses make decisions, serve customers, and manage operations.
• Prototype fast. Iterate faster. You'll test, fail, learn, and ship production-grade AI agent flows that power real business outcomes.
• Collaborate with product and design to identify high-impact user journeys where AI can be a 10x unlock — and then build them.
• Push the limits of RAG, embeddings, and vector search to bring real-time, grounded intelligence into every agent decision.
• Engineer smart integrations with OpenAI, Anthropic, Claude, and other LLMs — blending in enterprise APIs, CRMs, internal tools, and more.
• Lead development of multi-agent orchestration flows: planner-executor models, memory layers, persona-based behaviours, and tool-using agents.
• Own the AI pipeline end-to-end: prompt engineering, dynamic context handling, agent simulation and evaluation, all the way to deployment and monitoring.
• Help set the bar for reliability, latency, and safety of AI outputs — your work will shape how users trust AI inside their organisations.
• Work alongside curious, driven people who care deeply about shipping transformative products, not just academic demos.

Requirements:

• Bachelor's degree in Computer Science or equivalent practical experience.
• 8+ years of hands-on experience in applied machine learning, NLP, or AI system development, particularly with LLMs and agentic frameworks.
• Deep familiarity with large language models such as GPT-4, Claude, or similar, including prompt tuning, fine-tuning, or API-based deployment.
• Hands-on experience with Retrieval-Augmented Generation (RAG) pipelines using vector stores and embeddings.
• Knowledge of multi-agent systems, task orchestration, and related architectures.
• Proficiency in Python and modern ML frameworks (e. g., PyTorch, TensorFlow).
• Experience integrating with agent orchestration frameworks like LangChain, LangGraph, Temporal, n8n, or custom stacks.
• Solid understanding of enterprise software principles, including version control, CI/CD pipelines, API design, and performance monitoring.
• Excellent communication and collaboration skills; ability to thrive in a fast-paced, startup environment with evolving priorities.