Lead AI Engineer

Brillio

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

Posted 9/18/2026full-timeBangalore • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in full-stack development, particularly with React, Angular, or Vue for frontend and Node.js, Java Spring Boot, or Python for backend. Proficient in cloud-native solutions on Azure, AWS, and GCP, with a strong focus on agentic AI frameworks and microservices architecture.

Highest-signal resume keywords

Full-Stack DevelopmentCloud-Native SolutionsAgentic AI FrameworksMicroservices ArchitectureCI/CD Pipeline Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Full-Stack Data ScienceFrontend DevelopmentBackend DevelopmentRESTful API DesignMicroservices ArchitectureDocker ContainersKubernetesPrompt EngineeringRetrieval-Augmented GenerationEvent-Driven Architecture

Soft Skills

CollaborationProblem-Solving

Tools & Technologies

AzureAWSGCPLangChainLlamaIndexSemantic KernelAutoGenCrewAIFAISSKafka

Certifications & Qualifications

Cloud Platform CertificationFull-Stack Development CertificationAI Framework Certification

Industry Keywords

Agentic AIMicroservicesEvent StreamingFederated LearningPrivacy-Preserving Algorithms

Tech Stack

Tools & technologies

AngularAWSAzureCloudDjangoDockerGoogle Cloud PlatformJavaJavaScriptKafkaKubernetesMicroservicesNode.jsPythonReactSpringSpring BootSpringBootVue.js

About the role

Key responsibilities & impact

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
Develop cloud-native solutions on Azure, AWS, and GCP
Integrate LLM-based frameworks and agent orchestration tools
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

Requirements

What you’ll need

At least 2 to 4 years of experience in full-stack data science, including practical exposure to cloud-native architectures and agentic AI frameworks
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
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related discipline
Preferred: familiarity with vector databases such as FAISS or Pinecone
Preferred: knowledge of event streaming systems like Kafka or Pub/Sub
Preferred: experience with federated learning or privacy-preserving algorithms
Preferred: contributions to open-source projects or AI/ML or full-stack hackathons
Preferred: experience with Domino Datalabs or Databricks ML
Cloud platform certification, full-stack development certification, or AI framework certification listed as desired qualifications