Job Description

Are you passionate about building real-world AI solutions and working with fast-moving global startups?

Were looking for AI/ML Engineers who can bridge the gap between theory and practical deployment engineers who are eager to build, deploy, and scale AI systems that power real-world products.

In this role, you'll gain hands-on exposure to applied AI, MLOps, and cloud deployment, while collaborating with international teams and contributing to innovative, high-impact projects across global tech ecosystems.

Job Responsibilities

• Architect and develop advanced systems for AI research, agent workflows, and cognitive tools.
  
• Design and optimize LLM inference flows, embeddings pipelines, and RAG architectures.
• Integrate LangChain/LangGraph with vector databases and LLM runtimes.
  
• Implement graph reasoning layers using GraphDBs (Neo4j, Memgraph).
• Build MCP tools and multi-agent (A2A) communication pipelines.
• Collaborate with research teams to operationalize experiments and technical explorations.
• Maintain engineering excellence through documentation, testing, security, and code quality.
• Contribute to system design reviews, architecture discussions, and R&D investigations.

Job requirements

• Strong experience with LLM systems, embeddings, RAG flows, and inference pipelines.
• Advanced proficiency with LangChain, LangGraph, and agent orchestration tools.
• Deep knowledge of vector databases and graph reasoning systems.
• Expertise in designing distributed, AI-integrated software architectures.
• Strong engineering discipline, documentation, and secure code practices.
• Comfort working in experimental and research-first engineering environments.
• Strong experience in React/Next.js (Frontend) or Python/Node.js (Backend) is required. Proficiency in both will be considered a significant advantage, in addition to the AI-focused skill set outlined above.