About the job
Join Reaktor's Award-Winning Tech Community as an AI Developer!
Are you passionate about leveraging advanced AI technologies to create innovative LLM-powered applications? Do you excel in navigating the complete software development lifecycle? If you're eager to tackle real-world challenges with a holistic approach, we invite you to connect with us. Experience a collaborative, low-hierarchy environment where your ideas and curiosity can drive meaningful change.
Your Role as an AI Developer
As an AI Developer at Reaktor, you will take on a pivotal role, mastering various AI-related software development tasks that span from front-end design to production implementation.
Key Responsibilities:
Crafting and deploying end-to-end LLM-enabled applications, focusing on backend architecture and user-facing components to ensure scalability and maintainability.
Integrating both commercial and open-source LLMs (such as OpenAI, Anthropic, Meta Llama) into production applications using APIs or fine-tuning techniques.
Engaging with end-to-end RAG pipelines, including embeddings, vector databases (like PostgreSQL + pgvector, chromaDB, pinecone), and robust prompt engineering strategies.
Developing and implementing evaluation pipelines to measure model performance and ensure safety.
Collaborating with cross-functional teams to create AI use cases that address complex business problems.
Partnering with client tech and business teams to identify the most suitable technologies for their needs.
Providing world-class technical expertise to clients and team members.
Contributing to overall software architecture and design, including test automation and debugging tasks.
Your Profile
You are a curious AI developer adept in working with LLMs, backend and frontend technologies, with a solid understanding of infrastructure and transformer-based models.
Qualifications Required:
Proven experience in AI software development technologies including LLMs, backend, frontend, and operational skills within a production setting.
Experience in deploying AI applications in cloud environments (Azure, AWS, GCP) with containerization and orchestration tools (Docker, Kubernetes).
Strong problem-solving skills and a proactive approach in technology selection suitable for project needs.
