AI Lead Engineer
atsMantra
- Location
- Gurugram, Haryana, India
- Job type
- Full-time
Required skills
- LangChain
- Python
- AWS
- Artificial Intelligence
- Azure
- cross-functional
- GitHub
- machine learning
- NodeJS
- ReactJS
- TensorFlow
- Pytorch
About the role
Website:
atsmantra.com
Job details:
Key responsibilities include:
- Lead the design and development of AI native applications using tools like GitHub Copilot, Augment Code, and other AI-assisted development tools.
- Experienced in leveraging cloud AI services and LLMs, like Azure AI services, Azure OpenAI, Vector Stores etc.
- Able to develop and manage AI Agents and Agentic AI workflows using LangChain, LangGraph, and other leading platforms.
- Design and develop MCP servers to orchestrate multi-agent collaboration and task execution.
- Collaborate with product and engineering teams to translate business requirements into scalable AI-powered solutions.
- Guide the team in integrating AI capabilities into business applications, ensuring performance, security, and maintainability.
- Mentor junior developers and foster a culture of innovation and continuous learning.
- Stay current with emerging trends in AI development, including newer LLM Context techniques and Agentic AI.
Requirements:
- Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field
- 8 years of experience with a minimum of 2+ years of cumulative experience in the field, demonstrating a strong foundation in AI technologies.
- Experienced in designing and developing enterprise-grade applications.
- Strong proficiency in ReactJS, NodeJS, Python, and experience with machine learning.
- Excellent problem-solving skills and ability to work effectively in a fast-paced environment.
- Strong communication and teamwork skills, with the ability to collaborate effectively with cross-functional teams.
Nice to have:
- Experience with fine-tuning machine learning models using frameworks like TensorFlow, PyTorch, AutoTrain, ChromaDB, and LoRA Weights.
- Experience with deploying AI applications & models in cloud environments (e.g., AWS, Azure) and optimizing their performance for production use.
- Researching and experimenting with different Generative AI techniques and incorporating them into solution offerings
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