Technical Lead

Crystal Peak; Dadri; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Crystal Peak is seeking a Technical Lead for AI & Platform Services in Noida. You will lead design, development, deployment and production ownership of scalable backend and AI-enabled services.

The role requires strong Python expertise, experience with event-driven architectures, and cloud technologies including Azure. You will collaborate with AI engineers, DevOps and AIOps teams to ensure reliability and performance in production.

Qualifications

• 7+ years of software engineering experience.
• Strong hands-on Python experience; Java/C#/Go or similar are a plus.
• Strong understanding of microservices, distributed systems and REST APIs.

Responsibilities

• Lead architecture, design and development of scalable backend services and APIs.
• Mentor engineers and provide technical direction on architecture, performance and security.
• Own production reliability, logging, monitoring and release management.

Skills

Python

Azure

Kubernetes

Kafka

Redis

Docker

CI/CD

AI/LLM

Event‑driven

Tools

AKS

Job description

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:

• 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.
• 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.
• 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:

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