About the Role

We are hiring for AI Engineer with hands on experience to develop AI enabled solutions and services and integrate autonomous AI agents and local LLM pipes into our enterprise HRMS platform. You will build on-premise and cloud-deployable AI tools using local inference engines, multi-agent frameworks, and FastAPI microservices or similar other tools.

Skills Required:

- Experience: 2+ years of hands-on experience in AI/ML Engineering, Generative AI, or a related field.
- Education: Bachelor s degree in Computer Science, Engineering, Data Science, AI, or a related field.
- Strong proficiency in Python and familiarity with PyTorch, TensorFlow, Scikit-learn, FastAPI, Flask, and OpenAI APIs.
- Hands-on experience with Generative AI, LLMs, RAG, embeddings, prompt engineering, and fine-tuning .
- Robust understanding of AI Agents & Agentic AI and frameworks such as LangChain, LangGraph, LangSmith, AutoGen, or CrewAI .
- Practical experience with LLM inference and serving using vLLM, Ollama, LiteLLM , or similar tools for On-premise deployments.
- Experience building AI chatbots, intelligent applications, and AI-driven solutions for existing product and new solutions
- Knowledge of cloud deployment on AWS, Azure, or GCP.
- Familiarity with Grafana, monitoring dashboards, token management, and AI observability .
- Strong problem-solving, communication, and teamwork skills, with the ability to work on client-facing projects.
Must have knowledge of security and data protection and guardrails for LLMs

Roles and Responsibilities:





- Design and develop AI/ML and Generative AI solutions using LLMs, RAG, embeddings, prompt engineering, and fine-tuning.
- Build AI agents and intelligent applications using LangChain, LangGraph, LangSmith, AutoGen, CrewAI, or similar frameworks.
- Develop and deploy AI Agents, Chatbots, APIs, and AI-powered services using Python, FastAPI, Flask, or equivalent technologies.
- Work on LLM inference, quantization, model serving, optimization, and token management
Should be able to handle On-premise deployment of vLLM, Ollama, LiteLLM, or similar tools.
- Deploy AI solutions on cloud servers and support production implementation.
- Build monitoring and management dashboards using tools such as Grafana.
- Develop prediction models and dynamic analysis tools for existing applications based on requirements.
- Manage data pipes for data collection, transformation, and quality .
- Implement AI evaluation, monitoring, accuracy, security, reliability, and observability mechanisms.
- Collaborate with software engineers, data scientists, and solution architects to take AI solutions from experimentation to production.
- Stay updated with developments in GenAI, Agentic AI, LLMs, inference, and AI evaluation frameworks .

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI Engineer (Jaipur)
🏢 Timelabs
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