We are looking for a highly skilled Senior Full-Stack AI Engineer who can independently build and maintain the entire AI stack — from server infrastructure to optimized LLM/VLM deployment and integration. This role is ideal for someone who thrives in complex technical environments, understands how to make AI systems run fast and reliably, and is able to combine ML engineering, backend development, and DevOps expertise.

Our product focuses on home monitoring and smart-home safety systems - detecting risks such as water leaks, appliance failures, HVAC issues, abnormal humidity levels, and various environment-based threats. You will join a strong, established engineering team, working fully remotely.

What You Will Do

LLM/VLM & AI Systems Engineering

• Deploy, optimize, and maintain on-premise and cloud-based LLM and VLM models.
• Configure inference servers for maximum performance, reliability, and latency reduction.
• Perform fine-tuning, domain adaptation, and continuous improvement of existing ML models.
• Build and maintain RAG pipelines and AI agents for production use cases.
• Work with modern AI agent frameworks (LangChain, LangGraph, CrewAI, Autogen, LlamaIndex, etc.).
• Implement, configure, and maintain MCP Servers, tools, and integrations.

Infrastructure & Backend Engineering

• Configure, secure, and maintain Linux-based servers (both on-prem and cloud).
• Set up reverse proxies, networking, backend routing & API services.
• Build backend services in Java (Spring Framework) and Python.
• Containerize services with Docker and manage deployments end-to-end.
• Implement logging, observability, monitoring, and alerting systems.
• Build efficient CI/CD pipelines (Jenkins, GitHub Actions).
• Work with Kafka, NoSQL databases, and distributed systems.

DevOps & System Architecture

• Architect and maintain scalable, fault-tolerant infrastructure for AI and backend services.
• Debug and fix complex system issues across the stack (network, application, model).
• Apply best practices in cybersecurity and hardening of cloud/on-prem environments.

Cross-Team Collaboration

• Work in an Agile/Scrum environment, cooperating with AI researchers, backend engineers, and product teams.
• Drive experiments, R&D, and prototyping of new AI-powered features.
• Contribute to architecture design and long-term technical strategy.

Requirements

You are a strong fit if you have:

Technical Skills

• Strong expertise in deploying and optimizing LLMs/VLMs (on-prem + cloud).
• Advanced Python for ML engineering and AI tooling.
• Strong Java expertise (Core Java, Spring Framework, Maven).

• Hands-on experience with:

  • AI Agents, RAG systems
  • Docker, Linux, Git
  • Kubernetes is a plus but not mandatory
  • NoSQL databases
  • Kafka, Jenkins, GitHub

• Good understanding of:
  • Algorithms and data structures
  • Machine learning principles and model fine-tuning
  • Cybersecurity fundamentals (mandatory)

Infrastructure & DevOps

• Strong experience in configuring servers, networking, Nginx, and backend infrastructure.
• Deep understanding of deployment workflows, CI/CD, monitoring, and observability.
• Confident debugging of distributed systems and complex multi-service environments.

Bonus Skills

• Experience with IoT systems.
• Understanding of Z-Wave and ZigBee protocols (big plus).
• Familiarity with home automation or sensor-based monitoring systems.

Soft Skills

• Strong problem solver with the ability to choose the best solution rather than default tools.
• Works independently with minimum supervision.
• Communicates clearly in English (B2+).

What We Offer

• Fully remote position with flexible hours.
• Work in a technically strong environment with modern AI technologies.
• Opportunity to own the entire AI/ML infrastructure end-to-end.
• High impact on product architecture and AI capabilities.
• Long-term stability and a well-organized engineering culture.