AI Engineer

Job title: AI Engineer

About the Role Architect and build AI-native systems from 0 to 1, including autonomous agents and intelligent workflows. Own the full lifecycle of model quality—from experimentation and evaluation to production monitoring and continuous improvement, and design evaluation frameworks and agent orchestration.

What You'll Do

• Architect and build AI-native systems, autonomous agents, and intelligent workflows from 0 to 1.
• Design and implement agent orchestration frameworks (memory, planning, tool usage, self-reflection, and recovery).
• Own the full lifecycle of model quality—from experimentation and evaluation to production monitoring and continuous improvement.
• Design and build evaluation frameworks (offline benchmarks, online experiments, A/B testing).
• Monitor production AI systems for quality, latency, cost, and failure modes; drive iterative improvements.
• Rapidly experiment with models, prompts, and architectures; use structured evaluation to identify best solutions.
• Translate cutting-edge LLM capabilities into reliable, scalable production-grade systems.
• Collaborate with product, design, and full-stack engineers to shape AI-driven user experiences.
• Take ownership of AI features end-to-end—from research to deployment and monitoring.
• Help define best practices for AI-native products across the organization.

What We're Looking For

• Proven experience building and deploying production-grade AI systems.
• Strong software engineering foundation with 4+ years in backend or full-stack.
• Deep familiarity with modern AI tooling (LLM APIs, embeddings, vector databases, RAG).
• Hands-on experience designing evaluation and monitoring systems for LLM-based applications in production.
• Experience designing or working with agent-based systems (e.g., ReAct, tool use, multi-step reasoning loops).
• Strong understanding of system design, scalability, and reliability in distributed environments.
• Experience running structured experiments (e.g., A/B tests) and using data to drive decisions.
• Ability to navigate ambiguity and rapidly evolving technologies; strong communication and collaboration.

Nice to Have

• Experience building AI-native or agent-based products from scratch.
• Familiarity with LLM observability tools, tracing, and debugging workflows.
• Experience with real-time systems, WebSockets, or collaborative environments.
• Background in rapid prototyping, experimentation, or startup-like environments.

Compensation & Benefits

• Salary information not provided in the posting; benefits not specified.