Senior Software Engineer, Backend & AI Platform - Sureel AI

Design and build scalable backend services, APIs, data pipelines, and platform infrastructure across the Sureel stack.

Own systems end-to-end, from architecture and implementation through deployment, observability, debugging, and iteration.

Build infrastructure for high-volume AI, media, attribution, search, retrieval, and enterprise workloads.

Work with our AI team to move experimental models and algorithms into reliable production services.

Build and improve our MLOps capabilities across model deployment, inference, versioning, evaluation, monitoring, and reproducibility.

Own and improve DevOps and cloud infrastructure, including CI/CD, infrastructure-as-code, containers, orchestration, security, observability, and deployment reliability.

Build enterprise capabilities such as authentication, RBAC, multi-tenancy, auditability, bulk operations, integrations, and configurable workflows.

Make architecture decisions across databases, queues, caching, distributed systems, compute, storage, networking, reliability, and cost.

Work directly with Product and, when needed, customers or AI partners to turn complex requirements into scalable technical solutions.

Build internal tooling and automation that makes the entire engineering and research team more effective.

You are a senior software engineer with strong depth in backend and platform engineering and the ability to work across the stack when needed.

You have personally designed, built, deployed, and operated meaningful production systems.

You are highly proficient in a modern backend language and comfortable working extensively with TypeScript/Node.js. Python experience is a bonus.

You understand the fundamentals behind databases, networking, concurrency, APIs, distributed systems, queues, caching, cloud infrastructure, and failure modes.

You can go beneath frameworks and abstractions when necessary rather than treating them as black boxes.

You have strong cloud, DevOps, and production infrastructure experience.

You understand ML systems well enough to work effectively with model serving, GPU workloads, inference, data pipelines, embeddings, evaluation, and MLOps.

You use AI as part of your engineering workflow and look for practical ways to automate and accelerate your work.

You reason from first principles and enjoy working through difficult technical problems.

You care about the product and business outcome, not just the technical implementation.

You are comfortable in a fast-moving startup environment where you will have significant ownership and ambiguity.