sema4.ai
At Sema4.ai, we’re building an Enterprise AI Agent platform that fundamentally changes how knowledge work gets done—by enabling people and AI agents to collaborate in durable, trustworthy ways.
As a Staff Backend Engineer on the Agent Platform, you will be the engineering counterpart to the AI team. While the AI team designs and evolves the underlying cognitive architectures, you build the production systems, features, and workflows that turn those capabilities into customer-facing features and functionality.
This is an early, high-impact role. You’ll operate at the platform/product boundary, shaping how agents are configured, executed, observed, and scaled in real enterprise environments. Your work will directly determine whether our agents are not just intelligent—but usable, reliable, and operable at scale.
Agent Systems Engineer
You know how to turn LLM- and agent-based building blocks into real backend systems. You’re comfortable working one layer above raw cognitive primitives: orchestration, execution models, state management, failure recovery, permissions, and lifecycle management. You understand the sharp edges of agent systems and design defensively around them.
Platform-Oriented Builder
You think in terms of capabilities, not demos. You care deeply about APIs, contracts, defaults, and extensibility. You design systems that other engineers and customers can build on, reliably and easily.
Product-Minded Technologist
You work closely with product and design, and care deeply about how features are actually used. You translate product intent into durable backend abstractions and push back when necessary to protect system integrity, operability, or long-term velocity.
Engineer With Judgment
You move fast and with stability. You know when to prototype and when to harden. You think about failure modes, migrations, and operational realities early—even when requirements are still evolving.
Build Product-Grade Agent Infrastructure
Design and implement the backend systems that make agents usable in production:
execution engines, workflow orchestration, tool invocation frameworks, document processing systems, database interfaces, authentication and authorization, and lifecycle management.
Turn AI Capabilities into Features
Work closely with the AI team to consume new cognitive primitives and turn them into concrete, shippable functionality: agent behaviors, configuration models, execution semantics, and observability surfaces that customers can rely on.
Own Reliability, Scale, and Operability
Ensure agent-powered systems behave predictably under load and over time. This includes handling retries, partial failures, long-running workflows, cost controls, and performance tradeoffs. You’ll help define what “production-ready” means for agents.
Shape the Platform Surface Area
Influence API design, data models, and internal contracts to ensure the platform remains cohesive as it grows. You’ll help prevent accidental complexity and keep the system understandable and evolvable.
Contribute to Technical Leadership
Participate in design reviews and code reviews, help set engineering standards, and mentor other engineers. You’ll act as a force multiplier across the product engineering organization.
7+ years of backend software engineering experience in production systems
Deep experience building backend services in Python, including performance, reliability, and observability concerns
Hands-on experience working with LLM- or agent-based systems, especially orchestration, tools, or workflow execution
Strong product and systems thinking: you understand how technical decisions show up in user experience
Strong communication skills: whether you’re talking to colleagues, customers, or machines, you communicate clearly, concisely, and collaboratively
A high-ownership mindset: you care deeply about the systems you build, and you take responsibility for their long-term health
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