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 an Agentic AI Engineer based in India.
This is a hands-on, customer-facing opportunity to build the next generation of AI-powered products from early prototypes through production deployment. You’ll architect scalable Generative AI and agentic systems that solve complex enterprise problems and create measurable business value. The role combines solution architecture, advanced AI engineering, and direct collaboration with customers, product teams, and engineers. You’ll work with LLMs, multi-agent workflows, RAG, NLP, vector databases, and modern cloud-native architectures. Beyond implementation, you’ll help establish reliable AI practices around observability, responsible AI, performance, and lifecycle management. This role is ideal for an experienced ML/GenAI engineer who enjoys technical ownership, rapid experimentation, and turning emerging AI capabilities into production-ready solutions.
Accountabilities
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 for use cases including NL-to-SQL, autonomous task execution, and RAG.
Evaluate, customize, fine-tune, and optimize state-of-the-art large language models for specific business and technical requirements.
Design, implement, and own complete ML/GenAI pipelines covering training, deployment, monitoring, evaluation, and lifecycle management.
Build APIs, microservices, integration frameworks, and supporting infrastructure that embed AI capabilities into enterprise products.
Apply responsible AI principles to mitigate hallucinations, bias, reliability issues, and other risks associated with production AI systems.
Work directly with customers, product leaders, and engineering teams to translate business requirements into robust AI architectures and solutions.
Mentor engineers and contribute to the development of long-term AI platform strategies, engineering standards, and best practices.
Continuously evaluate emerging AI models, frameworks, infrastructure, and optimization techniques to improve product capabilities and performance.
Contribute to AI observability, monitoring, governance, and operational processes required to run reliable AI systems at scale.
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 and comparable 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, internal tooling, and AI application development.
Solid understanding of Transformers, CNNs, RNNs, and practical experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Experience with NLP, embedding models, vector databases, retrieval-augmented generation, and semantic search.
Hands-on experience with models and platforms such as OpenAI, Llama/Llama 2, Azure OpenAI, and other open-source LLMs.
Experience designing distributed, cloud-native architectures using microservices, REST APIs, and scalable integration patterns.
Proficiency with at least one major cloud platform, such as AWS, Azure, or GCP, along with experience using Docker and Kubernetes.
Practical MLOps/LLMOps experience covering model training, deployment, monitoring, evaluation, and lifecycle management.
Excellent communication skills and the ability to explain sophisticated AI concepts and technical decisions to non-technical stakeholders.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field.
Strong ownership mentality and the ability to thrive in a fast-moving startup or high-growth environment.
Preferred experience includes LLM fine-tuning using techniques such as LoRA, RLHF, or PEFT.
Knowledge of AI performance optimization techniques, including GPU/TPU acceleration, quantization, pruning, or distillation, is advantageous.
Experience with AI observability and monitoring tools, AI governance, or compliance frameworks such as GDPR and SOC 2 is a plus.
Prior consulting, solution architecture, or enterprise AI product delivery experience is highly desirable.
Experience in financial services, healthcare, or insurance is an additional advantage.
Benefits
Location: India — Remote.
Employment type: Full-time.
Compensation: ₹25,00,000–₹45,00,000 per year.
Opportunity to architect and build next-generation Generative AI and agentic AI products from prototype through production.
Hands-on exposure to LLMs, multi-agent systems, RAG, NLP, vector databases, and modern AI engineering frameworks.
Customer-facing role offering direct exposure to enterprise AI architecture, business requirements, and solution design.
Opportunity to influence long-term AI platform strategy and engineering standards.
Collaboration with product, engineering, and customer teams in a fast-paced technology environment.
Opportunities to mentor engineers and expand technical leadership responsibilities.
Exposure to modern cloud-native infrastructure, MLOps/LLMOps, AI observability, and responsible AI practices.
High degree of technical ownership and autonomy in a rapidly evolving AI environment.
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
No