AuxoAI - Senior AI Engineer - LLM / Generative AI

Job Description :

AuxoAI is seeking a skilled and experienced AI Engineers to join our dynamic team. The ideal candidate will have 7+ years of prior experience in software engineering, with 2+ years of experience in AI / ML (with expertise in Generative AI and LLMs). This role involves collaborating with cross-functional teams to drive innovation and deliver impactful AI-driven products.

This role is responsible for implementing our strategic direction on AI, intelligent automation, and data-powered operations. This role will also guide the implementation of AI solutions across various projects, with an eye on AI :

• AI / ML Solution Development : Design, develop, and deploy AI / ML technology stacks from concept to production and deployment
• Technical Leadership : Provide technical leadership and mentorship to junior engineers, guiding them in best practices and advanced techniques.
• Develop and optimize Generative AI workflows, including prompt engineering, fine-tuning, RAG and LLM-based applications.
• Work with Large Language Models (LLMs) such as Claude, Llama, Mistral, and GPT, ensuring efficient adaptation for various use cases.
• Design and implement AI-driven automation using agentic AI systems and orchestration frameworks like Autogen, LangGraph, and CrewAI.
• Leverage cloud AI infrastructure (AWS, Azure, GCP) for scalable deployment and performance tuning.
• Collaborate with cross-functional teams to deliver AI-driven solutions.
• Front ending customer discussions, customer engagement and success stories
• Collaborate with stakeholders to gather requirements and translate them into technical :
• Bachelors in computer science, Engineering, or a related field
• Overall 7+ years experience in software engineering, with 2+ years of experience in AI / ML, with expertise in Generative AI and LLMs
• Experience with AWS Bedrock or Azure OpenAI studio or similar enterprise AI environments
• Strong proficiency in Python and experience with AI / ML frameworks like PyTorch and TensorFlow
• Experience with containerization (e.g., Docker, Kubernetes), version control systems (e.g., Git) and software development methodologies (e.g., Agile, Scrum)
• Knowledge of advanced prompt engineering techniques
• Experience in AI workflow automation and model orchestration
• Hands-on experience with API development using Flask or Django

(ref : hirist.tech)