: Lead Engineer AI Platform

About the Role

We are looking for an experienced Lead Engineer AI Platform to lead the design, development, and delivery of next-generation AI-powered applications. The ideal candidate will provide technical leadership, mentor engineering teams, and drive the development of scalable, secure, and high-performance cloud-based solutions powered by contemporary AI technologies.

This is a hands-on leadership role requiring expertise in software architecture, cloud-native development, AI integration, DevOps, and engineering best practices.

Key Responsibilities :

Technical Leadership

- Lead the architecture and technical design of AI-powered applications.
- Define engineering standards, coding guidelines, and development best practices.
- Review solution designs and conduct code reviews.
- Mentor and guide software engineers through technical challenges.
- Drive technical excellence and continuous improvement across engineering teams.
- Evaluate emerging technologies and recommend suitable solutions.

Software Development

- Design and develop scalable backend services using Python and FastAPI.
- Build secure, high-performance RESTful APIs and real-time communication services.
- Develop reusable, maintainable, and well-documented software components.
- Optimize application performance, scalability, and reliability.
- Troubleshoot and resolve complex production issues.

AI Platform Development

- Design and implement AI-powered features using Large Language Models (LLMs).
- Build Retrieval-Augmented Generation (RAG) solutions.
- Develop AI orchestration workflows and prompt engineering strategies.
- Implement conversation management and contextual memory.
- Integrate vector databases and semantic search technologies.
- Improve AI response quality, latency, reliability, and operational efficiency.
- Implement AI guardrails, monitoring, and responsible AI practices.

Cloud & DevOps

- Design cloud-native applications on Microsoft Azure.
- Build and maintain CI/CD pipelines using Azure DevOps.
- Improve deployment automation and release management.
- Monitor application health, availability, and performance.
- Collaborate with DevOps teams to enhance operational excellence.

Security & Quality Collaboration & Leadership

- Work closely with Product Managers, UX Designers, QA Engineers, AI Specialists, and other stakeholders.
- Participate in sprint planning, technical estimation, and release planning.
- Identify technical risks and propose mitigation strategies.
- Support recruitment, onboarding, and mentoring of engineers.
- Foster a culture of collaboration, innovation, and continuous learning.

Key Responsibilities Technical Leadership

- Lead the architecture and technical design of AI-powered applications.
- Define engineering standards, coding guidelines, and development best practices.
- Review solution designs and conduct code reviews.
- Mentor and guide software engineers through technical challenges.




- Drive technical excellence and continuous improvement across engineering teams.
- Evaluate emerging technologies and recommend suitable solutions.

Software Development

- Design and develop scalable backend services using Python and FastAPI.
- Build secure, high-performance RESTful APIs and real-time communication services.
- Develop reusable, maintainable, and well-documented software components.
- Optimize application performance, scalability, and reliability.
- Troubleshoot and resolve complex production issues.

AI Platform Development

- Design and implement AI-powered features using Large Language Models (LLMs).
- Build Retrieval-Augmented Generation (RAG) solutions.
- Develop AI orchestration workflows and prompt engineering strategies.
- Implement conversation management and contextual memory.
- Integrate vector databases and semantic search technologies.
- Improve AI response quality, latency, reliability, and operational efficiency.
- Implement AI guardrails, monitoring, and responsible AI practices.

Cloud & DevOps Design cloud-native applications on Microsoft Azure.

Build and maintain CI/CD pipelines using Azure DevOps.

Improve deployment automation and release management.

1. Monitor application health, availability, and performance.
2. Collaborate with DevOps teams to enhance operational excellence.

Security & Quality Collaboration & Leadership Work closely with Product Managers, UX Designers, QA Engineers, AI Specialists, and other stakeholders.

Participate in sprint planning, technical estimation, and release planning.

Identify technical risks and propose mitigation strategies.

Support recruitment, onboarding, and mentoring of engineers.

Foster a culture of collaboration, innovation, and continuous learning.

Required Technical Skills Programming

- Python
- Flask
- FastAPI
- REST APIs
- Asynchronous Programming

AI & Machine Learning

- Large Language Models (LLMs)
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agents and Agentic Workflows
- Vector Databases
- Embedding Models
- AI Evaluation and Monitoring

Backend Technologies

- Event-Driven Systems
- Authentication (OAuth2, JWT, SSO)
- WebSockets or Streaming APIs
- Redis (preferred)
- Message Queues (preferred)

Databases

- NoSQL databases (e.g., Azure Cosmos DB, MongoDB)
- Relational Databases
- Data Modeling
- Performance Optimization

Cloud & DevOps

- Microsoft Azure
- Azure App Service
- Azure Storage
- Azure Key Vault
- Azure Monitor
- Application Insights
- Azure DevOps
- Git
- Docker
- Kubernetes (preferred)

Experience

- 4+ years of professional software development experience.




- Proven experience designing scalable enterprise applications.
- Experience building AI-enabled or intelligent software solutions.
- Experience working in Agile development environments.

Leadership Competencies

- Strong architectural and technical decision-making skills.
- Excellent communication and stakeholder management.
- Mentoring and coaching engineering teams.
- Ownership and accountability.
- Strategic thinking with a pragmatic approach to delivery.
- Strong analytical and problem-solving abilities

.

Educational Qualification

- Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, or a related discipline.
- Equivalent industry experience will also be considered.

Nice to Have

1. Experience with AI observability and monitoring tools.
2. Knowledge of MLOps concepts and deployment pipelines.
3. Experience with educational technology or SaaS platforms.
4. Familiarity with OpenTelemetry and distributed tracing.

Experience integrating third-party APIs and enterprise identity providers.
- Python
- Flask
- FastAPI
- REST APIs
- Asynchronous Programming

AI & Machine Learning

- Large Language Models (LLMs)
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)

AI Agents and Agentic Workflows

- Vector Databases
- Embedding Models
- AI Evaluation and Monitoring

Backend Technologies

- Event-Driven Systems
- Authentication (OAuth2, JWT, SSO)
- WebSockets or Streaming APIs
- Redis (preferred)
- Message Queues (preferred)

Databases

- NoSQL databases (e.g., Azure Cosmos DB, MongoDB)
- Relational Databases
- Data Modeling
- Performance Optimization

Cloud & DevOps

- Microsoft Azure
- Azure App Service
- Azure Storage
- Azure Key Vault
- Azure Monitor
- Application Insights
- Azure DevOps
- Git
- Docker
- Kubernetes (preferred)

Experience

- 4+ years of professional software development experience.
- Proven experience designing scalable enterprise applications.
- Experience building AI-enabled or intelligent software solutions.
- Experience working in Agile development environments.

Leadership Competencies

- Strong architectural and technical decision-making skills.
- Excellent communication and stakeholder management.
- Mentoring and coaching engineering teams.
- Ownership and accountability.
- Strategic thinking with a pragmatic approach to delivery.
- Strong analytical and problem-solving abilities.

Educational Qualification

- Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, or a related discipline.
- Equivalent industry experience will also be considered.

Nice to Have

- Experience with AI observability and monitoring tools.
- Knowledge of MLOps concepts and deployment pipelines.
- Experience with educational technology or SaaS platforms.
- Familiarity with OpenTelemetry and distributed tracing.
- Experience integrating third-party APIs and enterprise identity providers.

📌 Lead Engineer (Bengaluru)
🏢 Tutorcloud
📍 Bengaluru