Senior Backend

Description

• Drive development and implementation of AI-powered features across the low-code platform

• Build and optimize AI agent pipelines leveraging leading language models and AI services

• Develop sophisticated agentic workflows to ensure high-quality AI responses using domain knowledge from low-code data sources

• Design and implement AI agent systems that generate and validate use-case specific workflows, user interfaces, and data schemas

• Create robust evaluation frameworks to measure and improve the quality of AI-generated outputs

• Collaborate with product and engineering teams to integrate AI capabilities into existing platform architecture

• Establish best practices for AI implementation, including monitoring, versioning, and continuous model improvement

• Mentor and share knowledge on AI agents systems within the team

Requirements

• Advanced degree in Computer Science or related field

• 8+ years of relevant experience in Backend Development

• Proven hands-on experience implementing AI agents workflows

• TypeScript/Javascript

• NodeJS

• Large Language Model integration (GPT, Claude, Gemini, Grok)

• Prompt engineering

• AI agents evaluation

• AI agents workflows pipeline design and implementation

• Git version control and prompt versioning management

• Cloud-based AI SDKs (GPT, Claude, Gemini, Grok)

• RESTful API design principles

• Database models designs

• Architectural patterns

• Basic understanding of authorization and authentication concepts within an AI agents environment

• Proven track record of implementing production-grade AI systems that deliver measurable business value

• Large Language Processing and Language Model (LLM) expertise

• Machine Learning Operations (LLMOps)

• Agents evaluation and optimization experience (deepchecks, openAI Evals, Langsmith and similar)

• Cloud computing platforms (preferably AWS)

• SQL querying and optimization

• ETL processing and integration

• RESTful API integration, management and design

• Software development best practices

• Implementing and fine-tuning large language models

• Building agentic centered workflow pipelines

• Developing generative AI applications

• Creating automated testing and validation frameworks for AI systems

• Documentation and knowledge sharing of AI agents systems

• Python and its ML/AI ecosystem (PyTorch, TensorFlow, Pandas or similar) (nice to have)

• FE experience (nice to have)

Benefits

• Offers Equity

• PTO

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