Senior AI Engineer

Senior AI Engineer| AI-Native Orchestration Platform

About NetSpeek
NetSpeek is building an AI-native orchestration platform for enterprise physical environments such as meeting rooms, AV stacks, collaboration devices, and hybrid work infrastructure.
Our AI, Lena, reasons over device state, retrieves structured knowledge, executes actions, and operates under enterprise constraints.

The Profile We Are Targeting
You come from a company where AI was the product, not a feature.
You have worked in a growth-stage AI SaaS environment where:

• Reliability mattered
• Evaluation was formalized
• AI performance was measured continuously
• Shipping velocity increased under scale pressure
• Customers depended on the system

What You Will Own

• Design and evolution of agentic reasoning flows
• Retrieval quality, embedding strategies, and grounding discipline
• Model evaluation pipelines and reliability metrics
• Hallucination detection and mitigation strategies
• Structured output design for safe action execution
• Human-in-the-loop escalation logic
• AI cost optimization under real usage patterns
• Model selection and experimentation discipline

You will work directly with:

• AI Team Lead for architectural direction
• EVP Product and Engineering for system-level strategy
• Backend engineers for execution integration
• UX for AI interaction flows
• This role shapes how intelligence behaves in our platform.

Requirements

• 5+ years in machine learning engineering or combination of 5+ years with ML and applied AI systems
• 2+ years building and shipping LLM-powered systems in a growth-phase AI SaaS company
• Hands-on experience with RAG systems including vector databases, embedding tuning, retrieval optimization
• Experience building evaluation pipelines for LLM performance and reliability
• Strong Python with production-level ML system implementation
• Experience operating under real product constraints such as latency, cost, observability, and safety

High Signal Indicators

• Experience designing agentic workflows with measurable performance improvements
• Exposure to AI-native startups that scaled from early traction to growth stage
• Experience reducing hallucination and improving grounding in production
• Cost optimization experience at scale including token modeling and caching strategies
• Familiarity with compliance-aware AI logging and enterprise requirements

What Senior Means at NetSpeek
You can:

• Translate ambiguous AI goals into structured system design
• Define evaluation before feature release
• Anticipate model failure modes
• Balance probabilistic reasoning with deterministic safeguards
• Improve systems iteratively using data
• Find solutions rather than pointing problems
• You are comfortable being accountable for AI behavior in production.

We are building a defensible AI orchestration layer.
The person in this seat will influence:

• How Lena reasons and acts
• How safe and reliable our automation becomes
• How scalable and cost-efficient our AI architecture is
• How strong our technical moat becomes

This is a foundational, high-leverage position inside an AI-native company that is scaling.