About the Role :
We're hiring a Senior AI Agentic Engineer to lead the development of autonomous AI agents that leverage LLMs, advanced memory architectures, and tool use orchestration. You'll be part of a cutting-edge AI team building intelligent systems that solve complex, real-world problems at scale.
The ideal candidate is a strong individual contributor with hands-on experience in AI / LLM-based applications and a solid background in software engineering (preferably in Python or Java). This role combines system design, agentic workflows, and orchestration frameworks like LangChain, ReAct, and LangGraph, with deep involvement in engineering best practices and scalable deployment.
Key Responsibilities :
- Design, develop, and deploy autonomous AI agents capable of multi-step reasoning and planning.
- Build and optimize memory and retrieval systems using vector databases and embeddings.
- Implement agent orchestration techniques (e.g., ReAct, CoT, LangGraph).
- Own architecture decisions - both HLD and LLD - and API design.
- Drive prompt engineering, fine-tuning, and continual performance improvement.
- Ensure AI safety, monitoring, observability, and risk mitigation strategies.
- Oversee cloud-native deployments using Docker, Kubernetes, CI / CD.
- Collaborate with product, design, and research teams to define and shape roadmaps.
- Mentor junior engineers and ensure high-quality code and documentation.
Must-Have Skills :
8-10 years of total experience in software engineering or applied AI roles.Strong programming skills in Python or Java.Experience building AI / ML-based products (preferably GenAI / LLM-based).Solid understanding of data structures, algorithms, and design patterns.Familiarity with frameworks like LangChain, LangGraph, or custom agent orchestration.Hands-on experience with vector databases, embeddings, and retrieval-augmented generation (RAG).Experience in prompt engineering, LLM fine-tuning, or using APIs like OpenAI, HuggingFace.Strong grasp of HLD / LLD, system design, and API architecture.Cloud deployment experience using AWS / GCP / Azure.Good to Have :
Exposure to AI safety and observability practices.Experience working in product-based companies or R&D teams.Contributions to open-source GenAI or agentic tools.Experience with LangSmith, Guardrails AI, or LangServe.(ref : hirist.tech)