Technical Lead

Role:Technical Lead-AI & Platform Services

Experience: 7+ Years

Location: Noida

Immediate Joiner

Role Overview:

We are looking for a Technical Lead- AI & Platform Services with strong hands-on software engineering experience to lead the design, development, deployment and production ownership of scalable backend and AI-enabled services.

The ideal candidate should have strong experience in Python, event-driven and queue-based architectures, pipeline/workflow orchestration, caching, cloud technologies and production reliability. Azure experience is preferred.

You will work closely with Software Engineers, AI Engineers, DevOps and AIOps teams and will co-own the reliability, performance and operational stability of services in production.

Key Responsibilities:

Software Engineering & Technical Leadership:

• Lead the architecture, design and development of scalable backend services and APIs.
• Remain hands-on with development, preferably using Python; Java or other enterprise languages are a plus.
• Conduct code and design reviews and establish good engineering practices.
• Mentor engineers and provide technical direction on architecture, performance, security and scalability.
• Identify and address technical debt and continuously improve the platform.

Event-Driven & Distributed Services:

• Design and develop event-driven, queue-based and asynchronous services.
• Work with technologies such as Azure Service Bus, Kafka, RabbitMQ, Event Grid or equivalent.
• Design reliable mechanisms for retries, dead-letter queues, idempotency, timeouts and failure recovery.
• Build services that can scale reliably with changing workloads.

Pipeline & Workflow Orchestration:

• Design and maintain business, data and AI processing pipelines.
• Orchestrate workflows across APIs, services, queues and AI components.
• Ensure workflows have appropriate retry, monitoring, failure recovery and scalability mechanisms.

Caching & Performance:

• Design and implement caching and in-memory data strategies to improve performance and scalability.
• Experience with Redis or similar distributed caching technologies.
• Address cache consistency, invalidation, TTL, memory usage and scalability considerations.

AI / LLM Services:

• Work closely with AI Engineers to integrate and productionize AI/LLM capabilities.
• Build reliable backend services around AI models and APIs.
• Support AI/LLM, RAG, agent and orchestration use cases.
• Ensure AI services meet production requirements for reliability, scalability, observability and performance.
• AI/LLM experience is preferred.

Cloud & Deployment:

• Design and deploy cloud-native services, with Azure preferred.
• Experience with AKS, Docker, Kubernetes, Azure Service Bus, Azure Functions, Key Vault and Azure Monitor/Application Insights is valuable.
• Work closely with DevOps on CI/CD, deployment, infrastructure, security and scalability.

Production Reliability & Ownership:

• Co-own production stability with DevOps/AIOps.
• Take accountability for service reliability, performance and operational health.
• Participate in incident resolution, RCA and permanent corrective actions.
• Establish appropriate logging, monitoring, alerting, metrics, tracing and health checks.
• Drive production readiness and post-release validation.
• Proactively identify reliability, performance and scalability risks.

Documentation & Release Management:

• Own and maintain technical documentation for services and platforms.
• Maintain architecture diagrams, API documentation, service dependencies, data flows, deployment procedures and operational SOPs.
• Maintain release notes and ensure changes are properly documented.
• Drive release readiness, deployment planning, rollback planning and post-release validation.

Security & Engineering Quality:

• Promote secure coding practices aligned with OWASP/SANS principles.
• Ensure appropriate protection of credentials, secrets, PII and sensitive information.
• Drive automated testing, code quality, dependency management and vulnerability remediation.

Required Skills & Experience:

• 7+ years of software engineering experience, preferably with significant backend/service development.
• Strong hands-on Python experience; Java/C#/Go or similar languages are a plus.
• Strong understanding of microservices, distributed systems, REST APIs, event-driven architecture and asynchronous processing.
• Experience with messaging/queue technologies such as Azure Service Bus, Kafka or RabbitMQ.
• Experience with Redis or equivalent caching technologies.
• Strong cloud experience; Azure preferred.
• Experience with Docker, Kubernetes/AKS and CI/CD.
• Strong production troubleshooting, observability and reliability experience.
• Good understanding of SQL/NoSQL databases and automated testing.
• Strong technical leadership, communication and problem-solving skills.

Preferred Experience:

• Experience building AI/LLM-powered applications or services.
• Experience working closely with AI/ML Engineers.
• Experience with LLM APIs, RAG, AI Agents or AI orchestration.
• Experience with Azure OpenAI or similar AI platforms.
• Experience with Infrastructure as Code and modern observability platforms.

What We Look For:

A strong ownership mindset—someone who can take a service from:

Design → Build → Test → Deploy → Monitor → Operate → Document → Improve

and take accountability for its technical quality, reliability and production stability.