Agentic AI Engineer
New
J
JobgetherArtificial Intelligence
India — RemoteFull-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
- PythonCloud ComputingKubernetesMachine LearningMLOpsGenerative AILangChain
Requirements
- 6+ years of experience in traditional Machine Learning, including at least 2 years of hands-on Generative AI experience.
- Strong practical expertise with LLMs, GPT models, prompt engineering, and agentic AI systems.
- Proven production experience with LangChain, LangGraph, or similar agentic AI frameworks.
- Strong Python skills, including API development, third-party integrations, and AI application development.
- Solid understanding of Transformers, CNNs, RNNs, and frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Experience with NLP, embedding models, vector databases, RAG, and semantic search.
- Hands-on experience with models such as OpenAI, Llama, and Azure OpenAI.
- Experience designing distributed, cloud-native architectures using microservices and REST APIs.
- Proficiency with at least one major cloud platform (AWS, Azure, or GCP) and container tools like Docker and Kubernetes.
- Practical MLOps/LLMOps experience covering training, deployment, monitoring, and evaluation.
- Excellent communication skills for explaining complex AI concepts to non-technical stakeholders.
- 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 initial concept and prototyping through production deployment.
- Design LLM-powered workflows, prompt strategies, reflexive systems, self-learning approaches, and multi-agent architectures.
- Develop intelligent AI agents using LangChain, LangGraph, or comparable agentic frameworks.
- Evaluate, customize, fine-tune, and optimize state-of-the-art large language models.
- Design, implement, and own complete ML/GenAI pipelines covering training, deployment, monitoring, and lifecycle management.
- Build APIs, microservices, and integration frameworks to embed AI into enterprise products.
- Apply responsible AI principles to mitigate hallucinations, bias, and reliability risks.
- Work directly with customers and product teams to translate business requirements into technical architectures.
- Mentor engineers and contribute to AI platform strategy and engineering standards.
- Evaluate emerging models, frameworks, and optimization techniques to improve performance.
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