Principal Software Engineer - Backend & Infrastructure

About the role

About Level AI

Level AI operates as a Series C conversational intelligence company with its headquarters in Mountain View, California. The organization is supported by funding from prominent venture capital firms and guided by operators from the Silicon Valley ecosystem. The company's platform analyzes every customer conversation using speech AI, natural language processing, and retrieval systems. This analysis converts millions of unstructured interactions into actionable decisions for the business.

Why This Role Exists

The company is currently at a scaling inflection point. The operational frameworks that enabled growth from Series A to Series C are insufficient for the next stage of evolution. This position is created to own that transition and define the architecture for future scale. You will serve as a Principal guiding technical strategy rather than merely building within existing constraints. You will set the technical direction for backend and ML infrastructure across multiple teams. Your primary responsibility involves making architectural decisions that are difficult and costly to reverse later. You will elevate the engineering standard across the organization through rigorous design reviews, active mentorship, and the tangible standards you set by example. You will report directly to the Vice President of Engineering. In this capacity, you will partner closely with Machine Learning, Product, and Infrastructure leads across the company's locations. You will work alongside engineers who have chosen to build here from Amazon, Google, and Meta because the problems are unsolved and the ownership is significant.

Location and Compensation

The role is based in Noida, India. This is a full-time engagement. The compensation package for this position is 450,000 INR per year.

Key Responsibilities

You will design the ingestion pipelines responsible for collecting customer interaction data from varied sources. Your work will establish the storage layouts and access patterns required to support rapid and complex query demands. You will institute code review practices that directly enhance implementation quality, reliability, and long-term maintainability. You will drive the delivery of improvements that strengthen system observability and operational stability. You will coordinate with partner teams to align infrastructure roadmaps and formalize integration contracts. You will refactor core services to meet scalability targets and reduce operational risk. You will guide architectural decisions for ML workflows to ensure their maintainability over the long term. You will evaluate new infrastructure options through a rigorous analysis of cost, performance, and reliability. You will lead the implementation of robust monitoring and alerting frameworks to detect issues before they impact customers. You will collaborate with data platform teams to optimize the cost and performance of data lakes and warehouses handling conversation data. You will define standards for API contracts and service communication to ensure interoperability across microservices. You will participate in on-call rotations to provide leadership during critical production incidents. You will mentor senior engineers and influence hiring decisions to build high-performing backend teams. You will conduct architecture review boards to validate major technical proposals and ensure alignment with long-term goals. You will translate business requirements into scalable technical solutions while balancing trade-offs between speed, cost, and complexity.

Requirements

You possess five or more years of experience building backend systems capable of handling high request volumes. You have a deep understanding of networking, storage systems, and distributed computing principles. You use Python or similar languages to implement services that operate reliably in production environments. You design systems that maintain high availability under heavy load and diverse failure scenarios. You are comfortable working in a fast-paced environment where requirements evolve based on customer needs and operational feedback. You communicate effectively with both technical and non-technical stakeholders to align on priorities and constraints. You demonstrate ownership by identifying problems, proposing solutions, and driving them to completion with minimal supervision. You adhere to engineering best practices including testing, documentation, and version control to ensure sustainable codebases. You have experience working with cloud infrastructure and infrastructure-as-code methodologies. You understand the fundamentals of machine learning pipelines and data workflows to collaborate effectively with ML engineers.

What you'll do

• Meet the bar Practical notes

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