Published on
Full-Time
Remote, Hybrid, or On-Site
Salary Negotiable
About the Role
AI Engineer
NetSpeek's Lena is the first Language Enabled Network Administrator built exclusively for operating multi-vendor networks of UC and Pro AV technologies. As a generative AI platform built from the ground up for enterprise-scale network operation, Lena automates much of the day-to-day administration of your UC and Pro AV network. Lena is a multi-lingual network administrator trained on a wealth of industry standards, platform-specific training, technical documentation and the operational history and context specific to your enterprise. Lena can autonomously monitor the network 24x7x365, observe when issues arise, investigate root causes, develop and execute resolutions, and generate reports to optimize both autonomous and human-driven workflows.
Overview
You have already touched real AI work. Production. Serious internal tooling. Something other people relied on.
You think about AI as something you build with, not just something you prompt. You have written Python that other people depended on. You know that an LLM call working once in a notebook is not the same as a system that holds up at 3pm on a Tuesday.
This role is open to people whose AI experience came from internal AI initiatives, internal tooling, or early production work. What matters is that you built something real and you understand why production AI is harder than experimentation.
Key Responsibilities
You will work alongside the AI Team Lead and senior AI engineers. You will own progressively larger pieces of the reasoning and retrieval layers as you grow.
Prompt iteration, structured output design, retrieval quality
RAG pipeline contributions: embedding workflows, grounding strategy
Evaluation and test pipelines for AI reliability
AI integration into platform services, alongside the backend engineers
Data preparation and AI response validation
Operational analysis of what Lena did in production, and why
You will pair often. With the AI Team Lead for mentorship and architecture. With senior AI engineers for review and design partnership. With backend engineers for the seams where AI meets the rest of the platform.
Technical Requirements
1 to 3 years of software engineering, ML engineering, or applied AI
Hands-on exposure to LLMs, RAG, or AI workflows beyond tutorials and courses
Strong Python fundamentals
Comfort with APIs, JSON, and modern SaaS systems
Familiarity with prompt engineering, structured output discipline, and modern AI tooling
Preferred Qualifications
Worked with vector databases or embedding pipelines
Exposure to LangChain, LlamaIndex, or comparable frameworks on something real
Internal AI tooling or automation that other people actually used
A working idea of what an LLM evaluation should measure
Startup or fast-moving product environment
Soft Skills
Proactive: Take initiative and drive projects forward while collaborating effectively with the team.
Continuous Learner: Passionate about staying current with emerging AI technologies.
Problem Solver: Brings an innovative approach to complex technical challenges
Featured Benefits
Medical insurance
Requirements Added by the Job Poster
• Authorized to work in the United States
