Senior AI Engineer

About NetSpeek: NetSpeek is the agentic control plane for enterprise physical infrastructure. We govern how AI agents reason about, decide on, and execute actions across highly complex enterprise endpoints. Our foundational reasoning and execution layer — Lena — sits natively within live production environments, where absolute operational reliability, continuous observability, and strict auditability are non-negotiable standards.

Role Summary

We are seeking a Senior AI Engineer to take end-to-end architectural ownership of Lena's core reasoning layer: retrieval orchestration, groundedness calibration, validation testing, and defining the strict boundary separating probabilistic AI behaviors from deterministic infrastructure actions. This is a high-leverage role for an applied practitioner ready to deploy enterprise-grade production agents operating under real safety, cost, and latency budgets.

Key Responsibilities

• RAG Pipeline Architecture: Design, optimize, and maintain advanced Retrieval-Augmented Generation (RAG) flows to ground diagnostic reasoning mechanisms inside high-volume structured operational telemetry, device state data, and deep system documentation.
• Production Evaluations: Construct and expand rigorous evaluation harnesses engineered to quantitatively calculate groundedness, minimize hallucination rates, manage refusal parameters, and trace action metrics on every codebase release.
• Execution Boundaries: Define and enforce safety parameters balancing probabilistic model decisions alongside the platform's underlying deterministic .NET infrastructure and audit tracking.
• Budget Optimization: Own and tightly monitor systemic token usage modeling, semantic caching layers, and latency/cost trade-offs per active workload.
• Cross-Functional Synergy: Partner directly alongside platform and .NET backend software engineers to land infrastructural changes and model weights safely inside enterprise client clouds.

Required Skills & Qualifications

• 5+ years of professional experience across Machine Learning engineering or applied AI software systems.
• 2+ years of hands-on experience building, scaling, and shipping production-grade LLM systems (agents, advanced RAG frameworks, structured data extractions, evaluation pipelines) within a growth-phase AI SaaS company where AI was the primary product.
• Deep operational exposure configuring vector databases, embedding model fine-tuning, and multi-stage semantic retrieval optimizations.
• Elite proficiency executing codebases using **Python** combined with clean, production-level system implementation principles.
• Proven capability managing systems bounded by tight operational constraints: multi-tenant scaling data safety, continuous compliance logging, and system telemetry.
• Comfortable taking absolute individual accountability for real-time AI model behavior inside customer production systems.
• Location Context: 100% remote eligibility open to qualified tech talent residing across the United States or Canada.

Strong Signals (Preferred Assets)

• Track record designing autonomous agentic workflows that yielded measurable performance improvements.
• Experience implementing cost optimization metrics at scale (token modeling, custom middleware caching).
• Familiarity with corporate compliance-aware AI logging structures and enterprise auditing requirements.
• Background working within an early or growth-stage AI-native tech startup.

What We Offer

• Flexible / unlimited time off configurations.
• Comprehensive corporate health insurance provisions.
• Direct equity participation structures (discussed transparently at the offer stage).
• Complete architectural ownership over a core system layer shipping to major enterprise environments.
• Licensed access to modern AI-assisted engineering accelerators (e.g., Cursor, Claude Code, GitHub Copilot).