Senior Agentic AI Engineer
New
J
JobgetherAI & IT
Based in IndiaFull-TimeSenior
Salary2,500,000 - 4,500,000 INR per year
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Job Details
- Experience
- 6+ years of experience in traditional Machine Learning, including at least 2+ years of hands-on Generative AI experience.
- Required Skills
- PythonKubernetesPyTorchTensorflowMLOpsGenerative AILangChain
Requirements
- 6+ years of experience in traditional Machine Learning, including at least 2+ years of hands-on Generative AI experience.
- Strong practical knowledge of LLMs, prompt engineering, and agentic AI systems.
- Hands-on experience with LangChain and LangGraph or comparable agentic frameworks.
- Strong Python development skills for API wrappers, integrations, and automation.
- Solid understanding of Transformers, CNNs, and RNNs with experience in TensorFlow, PyTorch, and Scikit-learn.
- Experience with NLP, embedding models, vector databases, and Retrieval-Augmented Generation (RAG).
- Practical experience with foundation models such as OpenAI, Llama/Llama 2, and Azure OpenAI.
- Experience designing distributed and cloud-native systems using microservices and REST APIs.
- Proficiency with AWS, Azure, or GCP, alongside Docker and Kubernetes.
- Experience with MLOps and LLMOps lifecycle management.
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or Statistics.
Responsibilities
- Architect and build scalable Generative AI and agentic AI applications from concept and prototyping through production deployment.
- Design sophisticated LLM-powered workflows, prompt strategies, reflexive systems, self-learning architectures, and multi-agent solutions.
- Develop intelligent AI agents using LangChain, LangGraph, or comparable frameworks for applications such as NL-to-SQL and RAG.
- Evaluate, select, customize, fine-tune, and optimize state-of-the-art LLMs for specific business and technical requirements.
- Design, implement, and own end-to-end ML/GenAI pipelines, including training, deployment, monitoring, and lifecycle management.
- Build robust APIs, microservices, and integration frameworks connecting AI with enterprise platforms.
- Apply responsible AI practices to address hallucinations, bias, reliability, and security risks.
- Work directly with customers and stakeholders to translate business requirements into scalable AI architectures.
- Design and implement distributed, cloud-native architectures for AI applications.
- Mentor engineers and contribute to long-term AI platform and engineering strategy.
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