Job Role : AI Engineer - Agentic AI

Experience : 3+ Years

Location : Bangalore

Employment Type : Full-Time

Job Summary :

We are looking for a hands-on AI Engineer - Agentic AI with 3+ years of experience in software/AI engineering and at least 1 year of hands-on experience in Agentic AI development. The ideal candidate will be responsible for building and deploying production-grade Agentic AI and multi-agent systems using modern LLM frameworks and cloud AI platforms.

Key Responsibilities :

- Design, develop, and deploy Agentic AI and multi-agent applications for enterprise use cases.

- Build intelligent AI agents and orchestration workflows using LangGraph and LangChain.

- Integrate and work with LLMs, prompt engineering, tools, memory, and agent workflows.

- Develop scalable and production-ready AI applications using Python.

- Integrate AI applications with enterprise systems through REST APIs, WebSockets, and event-driven architectures.

- Work with cloud AI platforms such as Azure AI Foundry, AWS Bedrock, or Google Gemini Enterprise.

- Develop integrations with enterprise data sources and source systems.

- Implement secure, reliable, and scalable enterprise AI application deployments.

- Build CI/CD pipelines using Jenkins and Git to automate application deployment.

- Monitor, troubleshoot, and optimize AI applications and agent workflows in production.

- Collaborate with product, engineering, data, and business teams to translate requirements into AI solutions.

Must-Have Skills :

- 3+ years of experience in AI/ML, software engineering, or related technologies.

- Minimum 1 year of hands-on Agentic AI development experience.

- Strong programming skills in Python.

- Hands-on experience with LangGraph and LangChain.

- Strong understanding of LLMs and Prompt Engineering.

- Experience building AI agents and multi-agent systems.

- Experience with at least one of : Azure AI Foundry, AWS Bedrock, or Google Gemini Enterprise.

- Strong knowledge of REST APIs, WebSockets, and event-driven systems.

- Experience with Jenkins CI/CD and Git.

- Experience deploying enterprise-grade AI applications.

- Strong experience in data integration and source-system integration.

Good to Have :

- Experience with RAG pipelines and vector databases.

- Knowledge of AI application security, governance, and responsible AI practices.

- Experience with containerization technologies such as Docker/Kubernetes.

- Experience with cloud-native architectures.

- Knowledge of observability and monitoring for AI/LLM applications.

- Experience working in Agile development environments.

Education :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, or a related field.