Lead Engineer - R01570935

Brillio 2

Bangalore +1 more

On-site

Who this role is best for

Frontend and backend engineers with AI coding experience and cloud expertise will find this role in Bangalore, India, aligning with their technical stack and infrastructure focus.

Best fit for

Candidates with 4–6 years of full-stack development experience and AI tool expertise in Angular and Python environments
— “at least 4 to 6 years of full-stack development experience, including hands-on expertise architecting and reviewing AI-generated code”
Professionals with strong API and database layer experience across GraphQL, RESTful, and cloud databases like DynamoDB
— “Guide AI tools to build and maintain robust API and data layers, including GraphQL schemas, RESTful APIs, and both relational SQL and DynamoDB databases”

Things to consider

This role likely demands a high level of autonomous responsibility and ownership of AI-generated code.
— “Direct autonomous AI coding agents to generate, refactor, and scaffold full-stack features”
The need for AI code auditing suggests a strong focus on security and reliability in cloud deployments.
— “Audit and validate AI-generated code for security vulnerabilities, performance bottlenecks”

How to stand out

Emphasize your experience with AI pair-programmers and customizing autonomous coding workflows in your resume.
— “Experience coding AI agents or customizing autonomous coding workflows”
Highlight your ability to optimize prompt engineering and ensure AI code accuracy in your interview responses.
— “optimizing prompt engineering to maximize code accuracy”
Demonstrate your hands-on experience with both Angular and Python in your portfolio or project descriptions.
— “hands-on expertise architecting and reviewing AI-generated code for cloud-native web applications”
Showcase your familiarity with cloud infrastructure and deployment practices for AWS and GCP.
— “Deep knowledge of AWS and GCP cloud infrastructure, deployment, and monitoring”
Demonstrate your ability to implement testing frameworks that eliminate AI code hallucinations.
— “Implement rigorous unit, integration, and end-to-end testing frameworks”

Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

Ensuring high test coverage
Optimizing cloud deployments

Typical background

Experience in full-stack developmentExpertise in AI pair-programmers

Skills & requirements

Required

Ai-generated CodeCloud-native Web ApplicationsAWS And GCP InfrastructuresGraphql SchemasRestful ApisDynamodb Databases

Preferred

Customizing Autonomous Coding WorkflowsAdvanced Cloud Security Practices

Stack & domain

Ai-generated CodeCloud-native Web ApplicationsAngularPythonGraphQLRestful ApisAWSGCPDynamodbSQLUnit TestingIntegration TestingEnd-to-end TestingCMS IntegrationGithub CopilotAntigravityKiroReact JSVue JSCi/cd PipelinesAutomated Deployment ToolsTeamworkProblem-solvingCommunicationAWS Certified Solutions ArchitectGoogle Professional Cloud ArchitectCertified Secure Software Lifecycle ProfessionalCloudWeb DevelopmentAI

About the role

Original posting from Brillio 2 via Lever

Lead Engineer
Job requirements:
Experience Range: With at least 4 to 6 years of full-stack development experience, including hands-on expertise architecting and reviewing AI-generated code for cloud-native web applications Key Responsibilities:
Direct autonomous AI coding agents to generate, refactor, and scaffold full-stack features across Angular and Python environments, ensuring rapid and accurate delivery
Audit and validate AI-generated code for security vulnerabilities, performance bottlenecks, and architectural alignment within AWS and GCP infrastructures
Guide AI tools to build and maintain robust API and data layers, including GraphQL schemas, RESTful APIs, and both relational SQL and DynamoDB databases
Engineer repository context, database schemas, and infrastructure requirements for AI tools, optimizing prompt engineering to maximize code accuracy
Implement rigorous unit, integration, and end-to-end testing frameworks to ensure high test coverage and eliminate AI code hallucinations
Monitor and optimize cloud deployments across AWS and GCP, ensuring high availability, scalability, and compliance with industry standards
Review and debug AI-generated logic, proactively addressing risks such as SQL injection, broken object-level authorization, and cloud misconfigurations
Integrate and manage CMS platforms within web applications, ensuring seamless content workflowsRequired Skills:
Advanced proficiency with AI pair-programmers and autonomous coding agents such as GitHub Copilot, AntiGravity, or Kiro
Expertise in Angular and TypeScript for frontend development
Strong experience with Python for backend development
Comprehensive understanding of GraphQL schema design and implementation
Proficient in RESTful API architecture and development
Hands-on experience with Amazon DynamoDB and relational SQL databases such as PostgreSQL or MySQL
Deep knowledge of AWS and GCP cloud infrastructure, deployment, and monitoring
Skilled in prompt engineering for AI code generation and repository context management
Experience implementing unit, integration, and end-to-end testing frameworks
Experience with CMS integration and management within web applicationsPreferred Skills:
Experience coding AI agents or customizing autonomous coding workflows
Proficiency with React JS or Vue JS for additional frontend flexibility
Expertise in advanced cloud security practices and compliance frameworks
Familiarity with CI/CD pipelines and automated deployment toolsDesired Qualifications:
Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a closely related discipline
Relevant certification such as AWS Certified Solutions Architect or Google Professional Cloud Architect
Certification in secure software development or web application security (e.g., Certified Secure Software Lifecycle Professional)

Source: Brillio 2 careers (Lever)