Agentic Engineer

Job Title: Agentic Engineer

Location: Noida

Experience Required: 48 years

About the Job

We are seeking a highly skilled and curious Agentic Engineer to join our AI team focused on building intelligent, autonomous agents powered by LLMs and multi-modal systems. This role involves designing, orchestrating, and deploying agents that can interact with tools, APIs, and users to solve real-world problems across domains.

The Agentic Engineer will be responsible for creating and managing autonomous agents that leverage large language models and external tools to perform complex tasks. This role requires a deep understanding of agentic frameworks, prompt engineering, and system integration. The ideal candidate will be passionate about building intelligent systems that go beyond traditional chatbots and can reason, plan, and act independently.

Responsibilities

Experience building or contributing to real-world autonomous agents that interact with external tools or APIs to perform tasksbeyond just chatbot development. This includes using agent frameworks to create systems that reason, plan, and act autonomously.

Design and develop autonomous agents using frameworks like LangChain, AutoGen, or similar.

Integrate agents with external tools, APIs, and data sources to enable complex workflows.

Collaborate with GenAI engineers, data scientists, and product managers to define agent capabilities.

Optimize agent behavior through prompt engineering, memory management, and feedback loops.

Ensure scalability, reliability, and performance of agentic systems in production environments.

Stay updated with the latest advancements in agentic architectures and LLM capabilities.

Mandatory Skills

Strong proficiency in Python and experience with LLM-based frameworks (e.g., LangChain, AutoGen, Semantic Kernel).

Hands-on experience with OpenAI, Anthropic, or similar LLM APIs.

Understanding of agentic workflows, tool calling, and memory/state management.

Experience with RESTful APIs, vector databases (e.g., FAISS, Pinecone), and embedding models.

Familiarity with prompt engineering and chain-of-thought reasoning.

Additional Skills

Knowledge of MLOps and deployment pipelines (Docker, Kubernetes, CI/CD).

Experience with multi-agent systems or agent simulation environments.

Exposure to GenAI models (text-to-image, code generation, etc.).

Understanding of ethical AI principles and bias mitigation.

Experience with cloud platforms (Azure, AWS, GCP).