# Lead AI Engineer I - R01571043 at Brillio

Lead AI Engineer I - R01571043 at Brillio in Gurgaon, Haryana, India. Hybrid. Posted September 10, 2026.

- Company: Brillio
- Location: Gurgaon, Haryana, India
- Workplace: Hybrid
- Experience: 2+ years
- Posted: 2026-09-10
- Apply: https://jobs.lever.co/brillio-2/d6bce3ce-09d9-49fc-9b49-0c87e5b82f76/apply
- Source: https://jobmagic.ai/jobs/lead-ai-engineer-i-r01571043-brillio-q2xy7w

## Requirements

- Design and develop end-to-end full-stack applications, covering frontend, backend, and API components
- Build and deploy agentic AI applications using multi-agent systems and autonomous workflows
- Implement scalable backend systems with microservices and event-driven architectures to support intelligent solutions
- Develop cloud-native solutions on platforms such as Azure, AWS, and GCP, ensuring robust and scalable deployments
- Integrate LLM-based frameworks and agent orchestration tools to enable adaptive and intelligent workflows
- Enforce best practices in code quality, testing, debugging, observability, performance optimization, security, and scalability
- Collaborate with cross-functional teams to deliver technical solutions aligned with business requirements
- Contribute to design reviews and architectural decisions for AI-driven systems
- Full-stack development with React, Angular, or Vue for frontend
- Backend development using Node.js, Java Spring Boot, or Python frameworks (FastAPI, Django)
- RESTful API design and microservices architecture
- Experience with Azure, AWS, and GCP cloud platforms
- Hands-on experience with Docker containers and Kubernetes
- CI/CD pipeline implementation
- Agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or CrewAI

## Description

**Analyst**

### Job requirements

**Experience Range:** With at least 2 to 4 years of experience in full-stack data science, including practical exposure to cloud-native architectures and agentic AI frameworks **Key Responsibilities:**

- Design and develop end-to-end full-stack applications, covering frontend, backend, and API components

- Build and deploy agentic AI applications using multi-agent systems and autonomous workflows

- Implement scalable backend systems with microservices and event-driven architectures to support intelligent solutions

- Develop cloud-native solutions on platforms such as Azure, AWS, and GCP, ensuring robust and scalable deployments

- Integrate LLM-based frameworks and agent orchestration tools to enable adaptive and intelligent workflows

- Enforce best practices in code quality, testing, debugging, observability, performance optimization, security, and scalability

- Collaborate with cross-functional teams to deliver technical solutions aligned with business requirements

- Contribute to design reviews and architectural decisions for AI-driven systems

**Required Skills:**

- Full-stack development with React, Angular, or Vue for frontend

- Backend development using Node.js, Java Spring Boot, or Python frameworks (FastAPI, Django)

- RESTful API design and microservices architecture

- Experience with Azure, AWS, and GCP cloud platforms

- Hands-on experience with Docker containers and Kubernetes

- CI/CD pipeline implementation

- Agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or CrewAI

- Prompt engineering and Retrieval-Augmented Generation (RAG) techniques

**Preferred Skills:**

- Familiarity with vector databases such as FAISS or Pinecone

- Knowledge of event streaming systems like Kafka or Pub/Sub

- Experience with federated learning or privacy-preserving algorithms

- Contributions to open-source projects or hackathons in AI/ML or full-stack domains

- Experience with model experimentation platforms such as Domino Datalabs or Databricks ML

**Desired Qualifications:**

- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related discipline

- Certification in cloud platforms (e.g., AWS Certified Machine Learning Specialty, Azure AI Engineer Associate, Google Cloud Professional Machine Learning Engineer)

- Certification in full-stack development or AI frameworks (e.g., Full Stack Web Development, TensorFlow Developer Certificate)

**Additional Information:** Location: Bangalore (Hybrid work arrangement)