Lead Engineer – Ai Platform

Job Description - Lead Engineer – AI Platform

Work Location: Bangalore

Employment Type: Full-time, Permanent

Experience: 4+ Years

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 modern 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.

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 Optimisation

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.