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
SeniorJob 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)