Astoria AI · 3 hours ago

Gen AI Software Developer

United States

Part-time

Remote

Senior Level

6+ years exp

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Software Development

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Responsibilities

Develop software applications from scratch using LLM-based tools and APIs (both closed- and open-source)

Collaborate with other members of our dev team on building reliable and scalable data pipelines for the platform

Work with the product team to develop application features according to project scope and requirements

Test and debug software applications to ensure high-quality, reliable software

Continuously improve the performance and scalability of software applications

Stay up-to-date with emerging LLM-based tools, techniques, and technologies

Collaborate with other developers to integrate LLM-based tools into the software development process

Qualification

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LLM-based toolsConversational AIPythonPrompt EngineeringNLPNLGNLUVector searchDSPyTypescriptGoCI/CDAutomated testingVersion control

Required

At least 6+ years of experience in software development, with recent focus on Prompt Engineering and LLM-based tools and APIs

Working knowledge of prompt programming (DSPy and other frameworks)

Bachelor's degree or higher in Computer Science or related field

Strong programming skills in Python, Typescript or Go

Experience with ChatGPT and other LLM-based tools, including pre-trained models and fine-tuning techniques

Familiarity with software development best practices, including version control, automated testing, and continuous integration/continuous deployment (CI/CD)

Excellent problem-solving skills and attention to detail

Ability to work independently and as part of a team in a quick-paced environment

Strong communication skills, both written and verbal

Proven ability and track record of building and deploying conversational AI systems (chatbots, virtual assistants) for multi-turn real-time user interactions

Experience in NLP, NLU, and NLG to handle complex user queries and provide intelligent, contextual responses

Knowledge of vector search and retrieval augmented generation (RAG) techniques to build graphs and search through vast amounts of user data