AI and LLM Solutions Engineer

4 days ago

Delhi, Delhi, India Jingle Infotech Limited Full time US$ 90,000 - US$ 1,20,000 per year

Key Responsibilities for an AI Solutions Engineer role focused on conversational AI and generative engines:

  • Design, develop, and deploy conversational AI solutions using ChatGPT, OpenAI, DeepSeek, Gemini, and other state-of-the-art generative engines for custom client applications.
  • Collaborate with cross-functional teams (business, technology, product) to tightly integrate chatbots and intelligent agents into new and existing digital platforms and workflows (web, mobile, cloud).
  • Customize and fine-tune large language models (LLMs) for client use cases, including advanced chatbots, business process automation, generative content workflows, analytics, and workflow optimization.
  • Experiment with prompt engineering, few-shot learning, and retrieval-augmented generationto continuously improve relevance, accuracy, and performance of conversational AI solutions.
  • Develop custom LLM models or pipelines where needed for specialized applications and industry verticals, leveraging open-source and commercial toolkits.
  • Troubleshoot and resolve issues related to NLP algorithms and machine learning models, including debugging code, optimizing accuracy, and ensuring scalability across enterprise use cases.
  • Stay up-to-date with the latest advancements in AI technologies, generative models, and platforms, and actively propose solution enhancements or adaptations based on new capabilities.
  • Integrate AI models/APIs seamlessly into client-facing digital products, ensuring secure, scalable, and efficient deployments aligned to project and business requirements.

Desired Candidate Profile

Required Skills & Experience

  • Hands-on experience building solutions using ChatGPT/OpenAI, Perplexity, DeepSeek, Gemini, or other LLM/AI platforms.
  • Strong proficiency in Python; experience with API integration and ML/AI libraries.
  • Familiarity with cloud AI platforms (Azure, AWS, Google Cloud) and orchestration.
  • Demonstrated ability with prompt engineering and rapid prototyping.
  • 1-4 years experience in AI application or solution development.
  • Proven track record in deploying LLM-powered systems or intelligent agents.

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