Job Description

Job Title : Agentic AI Engineer

Location : India (Remote)

Role Description This is a remote, contract role based in India for an Agentic AI Engineer. The person in this role will design, build, and optimize agentic AI systems, including multi-step workflows and autonomous agents that interact with tools, APIs, and data sources. Day-to-day responsibilities include developing and integrating neural network-based solutions, implementing and refining NLP pipelines, and building robust software components that enable reliable agent behavior. The Agentic AI Engineer will collaborate with cross-functional teams to translate requirements into technical designs, run experiments, analyze performance, and iterate on models and systems. The role also involves writing clean, maintainable code, documenting architectures and processes, and ensuring that solutions are secure, scalable, and production-ready.

Qualifications

Strong foundation in Computer Science and experience with Software Development, including coding best practices and version control.
Hands-on experience with Neural Networks and Pattern Recognition, with the ability to design, train, and evaluate machine learning models.
Practical skills in Natural Language Processing (NLP), including building and tuning pipelines, working with large language models, and integrating NLP into applications.
Familiarity with agentic AI frameworks, orchestration tools, or multi-agent systems, and experience integrating AI systems with external tools or APIs.
Proficiency in one or more programming languages commonly used in AI (such as Python), and experience with ML libraries and frameworks (e.g., PyTorch, TensorFlow, or similar).
Ability to work independently in a remote environment, manage priorities, and communicate clearly with technical and non-technical stakeholders.
Bachelor's or higher degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
Experience with cloud platforms, containerization, and MLOps practices is a plus, as is prior work on production-grade AI or agentic systems.