RocketHuntSmart job search
from 9,000 USD
per month
Reach out directly about this role
By job title
Full-time
Employment
Remote
Work Format
Lead
Grade
B2 - Upper-Intermediate
English Level
AI Engineering
Specialization
AI
Industry
Product company
Company Type
AI-Native Principal Engineer
🌎 Remote (from any country. оформление через b2b) 💰 From 9,000$ gross 🗣 Working language – English
Product – a global AI platform for content creation, translation, and localization (Fortune 500). Key investor – Matrix Partners. AI-first for 12+ years. 100+ engineers in 24 countries.
What you will be doing: About 80% of the time – hands-on in production: real code, real architecture, real limitations, real legacy that needs to be evolved, not rewritten.
Specific examples of impact that are already on the table: — Reinventing SDLC through agents. Taking work that usually takes days and rolling it out in hours – with production quality – by integrating AI into requirements, documentation, code, reviews, tests, and deployment. — Deconstructing a monolith with AI. Directing agents at 8–10-year-old legacy code, understanding it, and extracting valuable pieces into a modular, agent-friendly architecture. Requires a keen eye and a deep thinker who loves hands-on work. — Building autonomous engineering cycles. For example, a fully autonomous bug-fixing cycle: a bug appears → agents find the root cause in the code → propose and implement a fix → verify the result, and a human is involved only in the final decision. This is the foundation for automating engineering as a whole. — Designing a quality gate. Building an objective go/no-go signal provided by the system, not by engineer's intuition. This requires an engineering mind, not just a QA mind. — Changing how the team thinks. You set the standard through execution and help shift the engineering mindset of 100+ engineers in 24 countries.
What we expect from you:
— AI: deep production experience with LLMs, agents, and the modern AI stack. Ability to build multi-agent workflows, integrate AI into SDLC, assess autonomy boundaries, control costs, context, and security. Systemic thinking and real-world cases are important, not superficial ChatGPT usage. Relevant stack: MCP, RAG, LangGraph/LangChain/CrewAI, LLM observability, LiteLLM/OpenRouter, vector DB, Claude Code/Cursor.
— Engineering: hands-on experience with large-scale distributed production systems, AWS/Azure/GCP clouds, Kubernetes, Kafka, CI/CD, and observability. Experience with architectural solutions, legacy evolution, and mature system support is needed. Backend or fullstack; .NET is a plus.