Artificial Intelligence Engineer - LLM/LangChain

Core Skill :

AI Engineer

Mandatory Skills :

- AI/ML, Data Scientist, Python , LangGraph, LLM

Requirements :

- 4 -6 years of software engineering or AI/ML experience, with 2+ years in agentic or LLM-based system design.

- Hands-on experience with LangGraph, CrewAI, AutoGPT, BabyAGI, or similar frameworks.

- Proficiency in Python and common AI/LLM libraries (LangChain, OpenAI API, Hugging Face, etc.).

- Strong grasp of agent lifecycle, orchestration, and autonomy patterns (e.g., ReAct, Plan-and-Execute, hierarchical agents).

- Experience in integrating LLM agents with tools (APIs, search, file systems, databases) and managing secure, compliant interaction models.

- Solid understanding of vector stores , memory architectures, and context management strategies.

- Experience deploying agentic frameworks in large-scale enterprise environments (finance, telecom, healthcare, etc.) and Knowledge of LangGraph's stateful workflows will be a plus.

Role and Responsibilities :

- Architect and build a reusable, secure, and scalable Agentic AI framework that can be adopted by multiple teams across the enterprise.

- Define standards, patterns, and abstractions for building intelligent agents using LLMs and other foundational models.

- Leverage and extend frameworks like LangGraph, CrewAI, or Semantic Kernel to enable advanced agentic capabilities such as (Long-horizon task planning, Tool calling (APIs, databases, RPA, internal services), Memory persistence and retrieval (via vector stores or knowledge graphs),Autonomous decision-making and reflection,Multi-agent orchestration and collaboration, Human-in-the-loop workflows,Monitoring and observability,Governance and compliance,Security and access control,Performance optimization and cost management

- Collaborate with cross-functional teams to ensure the framework aligns with enterprise-grade expectations.

- Integrate the framework with existing enterprise platforms.

- Conduct research and stay updated on the latest advancements in Agentic AI, LLMs, and related technologies.

- Mentor and guide junior engineers in best practices for building agentic systems.

- Coach and guide engineering teams in adopting and extending the framework.