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216 of 472 matching · page 5 of 5

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Agent engineeringSeniorNew

Senior Engineer AI

Litmus7Trivandrum, Kerala, India

Posted 1d ago/Full-time/Expires Nov 10, 2026

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Why it matters

The role explicitly includes building and deploying real-world agentic AI applications using frameworks such as LangGraph and AutoGen. It combines agentic product development with NLP, model deployment, evaluation, monitoring, and scalable ML infrastructure.

About the job

Minimum 5 years of experience in machine learning engineering and AI development.
Deep expertise in machine learning algorithms and techniques like supervised/unsupervised learning, deep learning, reinforcement learning, etc.
Solid experience in natural language processing (NLP) - language models, text generation, sentiment analysis, etc.
Proven understanding of generative AI concepts like text/image/audio synthesis, diffusion models, transformers, etc.
Expertise in Agentic AI and building real world applications using the same.
Experience working with Agentic AI frameworks like Langgraph , ADK, Autogen etc.
Hands-on experience in developing and deploying generative AI applications (text generation, conversational AI, image synthesis, etc.)
Experience in MLOps and ML model deployment pipelines.
Proficiency in programming languages like Python, and ML frameworks like TensorFlow, PyTorch, etc.
Knowledge of cloud platforms (AWS, GCP, Azure) and tools for scalable ML solution deployment.
Experience with data processing, feature engineering, and model training on large datasets.
Familiarity with responsible AI practices, AI ethics, model governance and risk mitigation.
Understanding of software engineering best practices and applying them to ML systems.
Design, develop and optimize machine learning models for applications across different domains.
Build natural language processing pipelines for tasks like text generation, summarization, translation, etc
Develop and deploy cutting-edge generative AI & Agentic AI applications.
Implement MLOps practices - model training, evaluation, deployment, monitoring, and maintenance.

Stack

python
tensorflow
pytorch
aws
gcp
azure
langgraph
autogen

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