Note: The job is a remote job and is open to candidates in USA. Vaisesika is seeking a highly motivated AI Solutions Engineer to design, develop, and deploy AI-powered solutions that solve real-world business problems. The role involves collaborating with business stakeholders, data scientists, software engineers, and product teams to deliver scalable AI applications.
Responsibilities
- Design, develop, and deploy AI/ML solutions for enterprise applications
- Build and optimize applications using Large Language Models (LLMs) such as GPT, Claude, Gemini, or Llama
- Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases
- Create AI-powered chatbots, copilots, and intelligent automation solutions
- Integrate AI services with enterprise applications using REST APIs and microservices
- Fine-tune prompts and optimize LLM performance for business use cases
- Collaborate with business stakeholders to gather requirements and translate them into AI solutions
- Build scalable backend services using Python
- Deploy AI applications on cloud platforms (AWS, Azure, or GCP)
- Monitor model performance, optimize latency, and manage AI solution lifecycle
- Ensure security, governance, and responsible AI practices
Skills
- Experience: 8+ Years
- Experience in Generative AI
- Experience with Large Language Models (LLMs)
- Experience in machine learning
- Experience with cloud platforms
- Experience with API integrations
- Ability to design, develop, and deploy AI/ML solutions for enterprise applications
- Ability to build and optimize applications using Large Language Models (LLMs) such as GPT, Claude, Gemini, or Llama
- Ability to develop Retrieval-Augmented Generation (RAG) pipelines using vector databases
- Ability to create AI-powered chatbots, copilots, and intelligent automation solutions
- Ability to integrate AI services with enterprise applications using REST APIs and microservices
- Ability to fine-tune prompts and optimize LLM performance for business use cases
- Ability to collaborate with business stakeholders to gather requirements and translate them into AI solutions
- Ability to build scalable backend services using Python
- Ability to deploy AI applications on cloud platforms (AWS, Azure, or GCP)
- Ability to monitor model performance, optimize latency, and manage AI solution lifecycle
- Ability to ensure security, governance, and responsible AI practices
Company Overview