Job Description
Job Description
Full Stack Engineer - GenAI LLM
Experience : 5 - 20 Years
Location : North America - Permanent Remote
Must-Have :
- Experience with Microsoft OpenAI Azure or Google Vertex
- Experience developing GenAI applications (doesn't have to be professional)
- End-to-end full-stack application development
- Experience developing API endpoints in Python or Java
- Experience with PyTorch and / or TensorFlow
- Experience working with multiple AI Frameworks (hugging face, semantic search, RAG, etc)
Platform / Stack
You will work with technologies that include Microsoft OpenAI Azure, Google Vertex, PyTorch, and RAG Architecture.
What You'll Do As a Sr Software Engineer :
- Architect, design, and develop AI applications, integrating with Google Vertex, Microsoft OpenAI Azure, and other LLM suites
- Design and implement effective prompts, configure LLM settings, and optimize performance through prompt crafting, RAG, fine-tuning and other techniques
- Collaborate with cross-functional teams to define requirements, manage user expectations, and deliver high-quality AI solutions
- Develop and maintain API endpoints, front-end features, and full-stack applications that leverage LLMs and Generative AI models
- Implement AI applications that comply with ethical guidelines and legal standards, particularly regarding data privacy and user consent
- Integrate analytics and monitoring tools to track user interactions, application performance, and the efficiency of LLM integrations
- Mentor, motivate, and develop the technical capabilities of the existing engineering team
- Stay up-to-date with emerging trends and advancements in Generative AI, LLMs, and related technologies
Qualifications :
You could be a great fit if you have :
- 8+ years of experience in full-stack software development, with a strong focus on building enterprise-scale distributed and cloud or hybrid-cloud applications
- Regarded as an expert in the growing field of AI with 5+ years of experience developing AI solutions and prototypes, including Generative AI and LLMs
- Experience with PyTorch, TensorFlow, ONNX, LangChain, Kubernetes, and Docker
- Deep understanding of AI frameworks including Huggingface, semantic search, RAG, LLM agents, AgentGPT, orchestration, plugins, and LLM Ops
- Experience with Retrieval-Augmented Generation (RAG) architectures or frameworks like Langchain for building LLM-powered applications
- Proficiency in programming languages such as Python, Java, JavaScript, and experience with frameworks like React and Node.js
- Experience with cloud platforms such as Google Vertex, Microsoft OpenAI Azure, AWS, and Azure, using various solutions for developing integrations, APIs, and AI / ML applications
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