Locations

• Bulgaria
• Georgia
• Lithuania
• Mexico
• Moldova
• Poland
• Romania

Company Background

The client is a global leader in access solutions, known for its innovative products in the Smart Home and IoT space. Their portfolio includes smart garage door openers, locks, card readers, gates, and cameras, all integrated within a proprietary digital ecosystem. With a vast install base worldwide, the client is at the forefront of smart access technology, continuously evolving through AI and cloud innovation.

Project Description

The current initiative focuses on strengthening the AI infrastructure supporting object detection and generative AI models. Key areas include enhancing model validation scripts, automating model testing on edge devices, and modernizing data curation processes. The team aims to deliver high-performance, scalable solutions that ensure consistent model accuracy across diverse hardware platforms and improve real-time smart notifications. Emphasis is placed on system automation, AI model deployment, and the seamless transition from traditional object detection to generative AI-based features.

Technologies

• AWS
• Azure
• Databricks
• Apache Spark
• ML frameworks (TensorFlow, PyTorch)
• .NET Core
• Python
• NumPy
• Pandas
• Scikit-learn
• LangChain

What You'll Do

• Oversee the design, development, and deployment of AI features within clients' products such as: Video-based search using LLMs, Chatbot interfaces for search and AI-generated insight, backend pipelines and APIs for AI feature delivery.
• Architect and build agentic AI systems using LLMs, RAG, tool integration, and orchestration frameworks.
• Design role-based architectures where agents collaborate through coordination protocols and memory management.
• Build, test, and optimize pipelines using tools such as LangChain, LangGraph, and CAMEL.
• Develop systems for agent reasoning, planning, and long-term memory retrieval to enable contextual conversations and task execution.
• Work across product, engineering, and AI research teams to ensure scalable and performant deployment of assistants.
• Drive decision-making around tooling, infrastructure, observability, and production-readiness.
• Mentor engineers across the org in AI-native engineering patterns, architecture, and LLM ecosystem evolution.
• Ensure end-to-end delivery across frontend, backend, and ML components, and drive code quality, scalability, and maintainability best practices.

Job Requirements

• 10+ years of experience in software engineering, with at least 2+ years working with LLMs or agentic AI systems.
• Proven experience building LLM-powered agents that interact with external tools and APIs.
• Demonstrated work with agent orchestration frameworks (e.g., LangGraph, CAMEL, AutoGen).
• Experience leading cross-functional initiatives in AI productization, intelligent automation, or AI-native user interfaces.
• Experience in AI infrastructure, prompt engineering, or fine-tuning LLMs is a strong plus.
• Prior experience working in autonomous systems, virtual assistants, or cognitive agents is highly desirable.
• Video intelligence systems, Computer Vision is a strong plus.
• English level: B1+ (written and spoken).

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Internal startup incubator;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.