Staff Software Engineer, Backend / Agent Orchestration
Staff backend engineer at Wand to architect the distributed system that orchestrates its AI agent workforce: workflow execution on Temporal, sandboxed agent code execution, and Kafka/Kubernetes/Redis event pipelines running at scale. Pure backend, Go and Python, pairing with the India-based team's Tech Lead.
- Compensation
- Not disclosed
- Location
- India
- Work setup
- Remote
- Seniority
- Staff
- Employment
- Not specified
- Experience
- Not specified
- Category
- Backend
- Posted
Skills
Must have
- Real scalable distributed systems experience (production systems across many machines)
- Hands-on with Temporal or comparable workflow orchestration systems
- Strong with Kafka and Kubernetes for container orchestration, especially sandboxing components
- Deep backend engineering skills (no frontend work)
- Experience with distributed streaming and event-driven systems (Kafka, Redis)
- Track record of owning architecture end to end
- Strong in Go and Python
- Clear communicator who can design independently and bring the team along
- Exposure to agentic or LLM-based systems, especially tool calling
Nice to have
- Experience building safe, isolated execution environments (sandboxing)
- Background in process automation or RPA (BPMN, Camunda, UiPath, or similar)
- Exposure to distributed data stores such as Cassandra or ClickHouse
- Experience building infrastructure other teams can't live without
- On-call experience for distributed systems
- Time spent scaling infrastructure inside a fast-growing engineering org
Full description
Build the Future Workforce
Wand turns AI into labor. It enables humans and AI agents to operate together as a unified, hybrid workforce, with comprehensive management and oversight. And it’s already operating at scale inside some of the world’s largest organizations.
Wand built the world’s first Agentic Labor Infrastructure enabling governments and global enterprises to create, manage, and scale digital workforces.
Our mission is to integrate agent ecosystems into the core of work and business, unlocking a generational leap in the global economy. We’re building the infrastructure that lets humans and AI agents operate together safely, transparently, and at scale.
Join Wand in leading the Agentic Shift
Wand is building a high-performing global team who take full ownership of what they build. We lead by example, move fast, make data-aware decisions, and continuously push for more- always with a focus on delivering real value to customers.
You would be joining a world-class team that combines deep research expertise and real-world product execution, with experience spanning Deepmind, Google, Amazon, Miro, Elise AI, IBM and Accern.
Position Summary
Every agent on our platform runs because of what this team builds. We're hiring a Staff Software Engineer to help architect the distributed backend that powers agent orchestration at Wand: workflow execution on Temporal, sandboxed agent code, and the pipelines that keep thousands of agents running without falling over. Zero UI, zero fluff. Just hard distributed systems problems at real scale.
You'll pair directly with our Tech Lead on the India based team and take the architecture to the next level. We need someone who can turn "design v3 of this system" into a real, working plan, then help the team build it.
This isn't just about orchestrating a single agent. It's about orchestrating a workforce of agents working together through processes, and building the layer that makes that possible. Orchestration, task execution and tool calling, and sandboxing are largely independent pieces, so depth in any one of them matters more than breadth across all of them.
Role Responsibilities
- Architect the agent orchestration and workflow execution system on Temporal, including the sandboxing that keeps agent code execution, web access, and file systems locked down and safe.
- Build the task management, autonomous execution loops, and tool calling infrastructure that let agents run independently and act in the real world at scale.
- Own the distributed data and event pipelines (Kafka, Kubernetes, Redis) that keep the platform observable and resilient.
- Turn ambiguous, high stakes problems into concrete technical designs, ship them, and document the architecture so the next engineer doesn't have to guess.