Backend Platform Engineer

Who Connecteam is:

Connecteam is the leading platform for managing deskless teams, trusted by over 80,000 businesses worldwide.
We built Connecteam for real operators - the people running shifts, jobs, and teams across stores and sites. The kind of work that doesn’t happen behind a desk, and doesn’t have time for messy spreadsheets, scattered group chats, or tools that don’t talk to each other.
Connecteam brings daily operations and team communication into one intuitive app - from hiring and scheduling to training, tasks, and day-to-day coordination. It gives teams the clarity and control to run the day, shift after shift, job after job.
Backed by $220M+ from Insight Partners, Stripes, and Tiger Global, Connecteam is rapidly expanding worldwide - empowering frontline teams to work smarter, stay connected, and operate with greater efficiency.

About the role:

We are looking for an experienced and hands-on Backend Engineer to be a key player in building high-scale Data Platforms and Products for our business teams.
This role involves working with large datasets and scalable systems, and developing internal tools to enable data-driven decision-making across the company.
The team builds the backend systems and data infrastructure the rest of the company relies on: internal products, APIs, event pipelines, and integrations with external tools. The data comes from the full product, at the volume of over 1.7 million daily active users. The features are multi-system: an API, a pipeline, and often LLM-backed flows that have to stay correct in production.
LLMs and agents are part of the job. We use them to write, review, and debug code, and we ship them inside the product: agents and LLM features that other teams depend on.

Key Responsibilities:

• Develop internal tools and products for teams across Connecteam.
• Build and maintain services and APIs that support complex, multi-step workflows.
• Operate in a real-time, event-driven environment at high volume.
• Create and manage data pipelines, including the checks that keep data trustworthy.
• Design and ship LLM and agent features: tool use, prompts, evaluation, and the limits around cost, latency, and quality.
• Use coding agents as part of normal delivery, and raise the quality of what they produce.
• Take ownership of multiple systems and products.
• Work in a multi-cloud environment (Azure/GCP/AWS).
• Integrate third-party tools with our platform.
• Translate ambiguous business requirements into a technical plan and lead it through to production.