Senior Agentic AI Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Agentic AI Engineer based in India.
This is an opportunity to help architect and deliver next-generation AI products from early prototypes through production deployment. You will combine hands-on engineering with solution architecture and direct customer engagement. The role focuses on building sophisticated Generative AI and agentic systems, including multi-agent workflows, RAG solutions, and autonomous task agents. You will work with modern LLMs and frameworks such as LangChain and LangGraph while shaping scalable, cloud-native AI architectures. Your work will directly influence how AI capabilities are integrated into enterprise products and customer solutions. You will also help establish responsible AI practices, mentor engineers, and contribute to the long-term evolution of the AI platform.
Accountabilities
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 agentic frameworks for applications such as NL-to-SQL, autonomous task execution, 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 that connect AI capabilities with enterprise applications and platforms.
Apply responsible AI engineering practices to address hallucinations, bias, reliability, security, and other AI-related risks.
Work directly with customers, product teams, and engineering stakeholders to translate business requirements into scalable AI architectures and solutions.
Design and implement distributed, cloud-native architectures that support reliable and scalable AI applications.
Mentor engineers, contribute to technical direction, and help shape long-term AI platform and engineering strategy.
Stay current with emerging developments in agentic AI, Generative AI, LLMs, and AI engineering practices and apply relevant innovations to product development.
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, Generative AI, and agentic AI systems.
Hands-on experience with LangChain and LangGraph, or comparable agentic AI frameworks.
Strong Python development skills, including API wrappers, third-party integrations, automation, and internal tooling.
Solid understanding of Transformers, CNNs, and RNNs, with hands-on experience using TensorFlow, PyTorch, and Scikit-learn.
Experience with NLP, embedding models, vector databases, and Retrieval-Augmented Generation (RAG).
Practical experience working with OpenAI, Llama/Llama 2, Azure OpenAI, and other open-source or commercial foundation models.
Experience designing distributed and cloud-native systems using microservices, REST APIs, and scalable architectures.
Proficiency with at least one major cloud platform: AWS, Azure, or GCP, alongside experience with Docker and Kubernetes.
Experience with MLOps and LLMOps, including model training, deployment, monitoring, evaluation, and lifecycle management.
Strong communication skills, with the ability to explain complex AI concepts and technical solutions to non-technical customers and stakeholders.
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related discipline.
Strong ownership mindset and comfort working in a fast-paced, evolving environment.
Experience with LLM fine-tuning techniques such as LoRA, RLHF, or PEFT is a plus.
Knowledge of GPU/TPU acceleration, quantization, pruning, distillation, or other model performance optimization techniques is advantageous.
Familiarity with AI observability and monitoring tools, AI governance, and compliance frameworks such as GDPR and SOC 2 is beneficial.
Prior consulting or solution-architecture experience delivering enterprise AI products is preferred.
Experience in financial services, healthcare, or insurance is an additional advantage.
Benefits
Full-time remote position based in India.
Annual compensation range of ₹25,00,000–₹45,00,000, depending on experience and qualifications.
Opportunity to work on next-generation Generative AI and agentic AI products.
Exposure to advanced LLMs, multi-agent architectures, RAG, AI automation, and cloud-native technologies.
Customer-facing responsibilities providing opportunities to influence real-world enterprise AI solutions.
High degree of ownership and autonomy within a fast-moving technology environment.
Opportunity to mentor engineers and contribute to long-term AI platform strategy.
Exposure to emerging AI engineering practices, including MLOps, LLMOps, responsible AI, and AI observability.
Opportunity for professional growth while working on technically challenging AI initiatives.
How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Work arrangement
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