AI Agent Engineer at Nethermind

We are a team of researchers and builders dedicated to helping developers and enterprises navigate decentralized systems. As a global organization with over 350 team members across 66 countries, we collaborate with industry leaders like the Ethereum Foundation, Starknet Foundation, and Lido to solve complex challenges in the blockchain space. We are currently looking for a Senior AI Agent Engineer to join our team and help us build sophisticated systems that automate internal functions and eventually scale into public platforms.

Responsibilities

• Conduct research and development to integrate Large Language Models into our core company operations.
• Design, prototype, and implement advanced LLM-based solutions that move from initial concept to production.
• Experiment with the latest AI tools and technologies to push the boundaries of what is possible.
• Collaborate with top-tier research professionals and engineers to tackle difficult technical problems.
• Keep pace with the rapidly evolving landscape of AI and machine learning, with a specific focus on LLM developments.

Must-haves

• At least 5 years of professional software development experience, with a strong preference for Python proficiency.
• Deep understanding of software architecture patterns and industry best practices.
• A proven history of delivering high-quality, production-grade software.
• An entrepreneurial mindset, characterized by a willingness to take ownership and solve problems independently.
• Strong analytical skills for designing experiments and validating results.
• Familiarity with modern AI tools such as ChatGPT, Claude, and Perplexity.
• A passion for innovation and a drive to share knowledge with the wider team.

Nice-to-haves

• Practical experience building LLM-based solutions, including prompt engineering or using frameworks like LangChain and LlamaIndex.
• Background in designing RAG solutions, working with vector databases, or implementing techniques like GraphRAG.
• Experience with model fine-tuning, self-hosting, or quantization.
• Awareness of security challenges inherent to LLMs, such as data poisoning and prompt injection.
• Active contributions to open-source projects on GitHub.

Benefits

• The flexibility of a fully remote work environment.