SDE Intern

Job highlights

• Were looking for a motivated and technically strong SDE Intern to join our engineering team
• full-stack experience is a plus
• Experience integrating with external APIs (REST,GraphQL,webhooks,etc.)
• . Good to Have .
• Experience building MCP (Model Context Protocol) servers
• Experience working within an agile team on meaningful work

About the Role

Were looking for a motivated and technically strong SDE Intern to join our engineering team. Youll work on robust systems and workflows that enable internal users and the overall development of the product. You will build backend services, integrate with external APIs, and collaborate with the team to meet their use cases. This is a hands-on role where youll have the agency to think and act to drive fast/iterative progress across multiple fronts.

What Youll Do

• Design and build backend services and APIs that are accessible, fault-tolerant, and well-tested.
• Integrate with third-party and internal APIs to extend product capabilities.
• Work with AI agents and LLM-powered workflows, applying sound engineering practices (testing, validation, guardrails) to ensure robustness
• Write and reason through unit and integration tests, thinking critically about coverage, edge cases, and failure modes.
• Collaborate with senior engineers on system design, service orchestration, and architectural decisions.
• Work with data stores and infrastructure tooling relevant to the stack.

What Were Looking For

Must Have

• A strong portfolio of personal or academic technical projects, with a clear backend focus (bonus if any are live or deployed).
• Proficiency in Python and/or a solid grasp of an end-to-end backend stack; full-stack experience is a plus.
• Experience integrating with external APIs (REST, GraphQL, webhooks, etc.).
• A testing mindset, ability to think about how to validate, test, and harden implementations rather than just writing code that works on the happy path.

Good to Have

• Familiarity with common backend tooling: SQL/NoSQL databases, Redis (caching), message queues (e.g. Kafka, RabbitMQ, SQS), and search platforms like OpenSearch/Elasticsearch
• Exposure to AI agents or LLM-based systems, with an understanding of how they work and where they can fail.
• Docker / container basics.
• Git and collaborative development workflows.
• Familiarity with any cloud provider (AWS, GCP, Azure).

Bonus Points

• Experience building MCP (Model Context Protocol) servers.
• Experience designing fault-tolerant or resilient workflows that can recover gracefully from failures without data loss (e.g. idempotent jobs, retry logic).
• General understanding of ML concepts, enough to engage meaningfully with product requirements and the models powering our systems.

What Youll Gain

• Ownership of features that are aimed at varying use-cases.
• Agency to take decisions to meet requirements.
• Exposure to modern AI/LLM engineering practices.
• Mentorship from senior engineers across backend, ML, and platform.
• Experience working within an agile team on meaningful work.