Description

You will architect secure, scalable, and observable distributed systems, integrating LLMs and GenAI capabilities into enterprise platforms.

This role is on-site.

Responsibilities

• Design and govern enterprise-scale backend platforms for high availability, performance, and cost efficiency.
• Architect inference systems including routing, batching, caching, and cost optimization for LLM integrations.
• Define service architecture standards, API contracts, and data contracts across development teams.
• Implement AI-augmented backend architectures with retrieval-augmented generation (RAG) and agent-based flows.
• Champion developer experience by improving CI/CD quality gates, test automation, and observability-first design.

Required Skills

• 12+ years of backend engineering experience with Node.js/TypeScript, Java/Kotlin, .NET, Python, or Go.
• Strong expertise in distributed systems, microservices, event-driven architectures, and consistency models.
• Hands-on experience with cloud platforms (AWS preferred; Azure/GCP acceptable) and infrastructure as code.
• Proficiency with data and streaming technologies: SQL, NoSQL, Kafka, and Redis.
• Experience integrating LLMs, prompt engineering, and AI quality metrics within enterprise applications.
• Deep understanding of system design fundamentals: caching, resilience patterns, fault tolerance, and security.
• Strong background in operational excellence, including observability, performance tuning, and incident response.

Preferred Skills

• Experience with API gateways, service mesh, and networking fundamentals.
• Knowledge of AI safety, governance, and responsible AI principles.

Key Skills

Education

Any Graduate