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.
- 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.
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