AI Engineer

NETSPEEK INC.
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote

Tech stack

.NET
Artificial Intelligence
Software as a Service
JSON
Python
Machine Learning
Software Engineering
Data Logging
React
Large Language Models
Prompt Engineering
Caching
Backend
Front End Software Development
Software Coding
REST
Automation Anywhere

Job description

  • Building and tuning RAG components: chunking strategy, retrieval scoring, prompt scaffolding, grounding heuristics.
  • Wiring evaluation harnesses that catch regressions on every release.
  • Working on the Python services that mediate between Lena and the rest of the platform.
  • Working with backend (.NET) and frontend (React) engineers to land AI-affecting changes safely.

Requirements

Do you have experience in Software coding?, * You have 1+ years of software / ML engineering experience.

  • You're advanced in Python.
  • You've shipped Python code that real users relied on (production or internal stakeholders).
  • You've worked hands-on with LLMs, RAG, or AI workflows beyond tutorials.
  • You're comfortable with REST APIs and JSON-based integrations.

You probably aren't a fit if

  • Your AI work is mostly coursework or side projects without production exposure.
  • You want a heavily structured environment with predefined work queues., Must-have
  • 1-3 years of software engineering, ML engineering, or applied AI experience.
  • Hands-on exposure to LLMs, RAG systems, or AI workflows beyond tutorials or coursework.
  • Strong Python fundamentals; you have shipped Python that other people relied on.
  • Comfort with REST APIs, JSON structures, and modern SaaS systems.
  • Familiarity with prompt engineering and modern AI tooling.

Strong signal

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

Benefits & conditions

We are growth-stage and fully remote, not late-stage. We invest in the work, the tools, and the people, not the manifesto.

What that looks like in practice:

  • Flexible / unlimited time off
  • Health insurance
  • Equity participation, discussed at offer
  • Fully remote
  • Architectural ownership of work that ships to real enterprise customers
  • Direct working relationships with the people setting platform strategy
  • A growth-stage platform where the decisions you make in your first year shape the product for years
  • AI-assisted tooling licensed by NetSpeek (Cursor, Claude Code, GitHub Copilot, or comparable)

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