173 open roles · MEC
Lead Engineer - R01570935
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Where you can work
Unspecified
Locations named in the listing
- Bengaluru, Karnataka, India
View location wording from the posting
Bangalore, Karnataka, India
Role overview
Extracted from the posting. Read the employer’s full description below.
What they are looking for
- 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
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- 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 workflows
- 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 applications
- 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 tools
- 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)
Employer description
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 workflows
Required 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 applications
Preferred 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 tools
Desired 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)
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