Software Engineer, Agent Systems

Normal Computing

Software Engineer developing backend runtimes and distributed systems for AI products at Normal Computing. Collaborating on orchestration services and execution environments with cross-functional teams.

Posted 7/30/2026full-timeNew York City • New York • 🇺🇸 United StatesMid-LevelSenior💰 $150,000 - $265,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in backend engineering, distributed systems, and API design, with a strong focus on building reliable orchestration services and execution environments for AI products. Proven ability to coordinate workloads, manage state across long-running sessions, and ensure production reliability and observability.

Highest-signal resume keywords

Backend Engineering FundamentalsAPI DesignDistributed SystemsKubernetesOrchestration Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

API DesignData ModelingConcurrencyDebuggingTestingDistributed State ReasoningFailure Modes AnalysisProduction Data SystemsOrchestration SystemsWorkflow Engines

Soft Skills

Pragmatic JudgmentSense of Ownership

Tools & Technologies

KubernetesPostgresRedisValkeyObject Storage

Industry Keywords

Backend SystemsDistributed SystemsProduction InfrastructureObservabilityMaintainability

Tech Stack

Tools & technologies

Distributed SystemsKubernetesPostgresRedis

About the role

Key responsibilities & impact

Build the backend runtimes and distributed systems behind our AI products.
Design orchestration services, execution environments, internal APIs, persistence layers, and observability systems that allow AI agents to perform long-running work reliably.
Coordinate workloads across distributed environments, execute code and tools securely, preserve state across long-running sessions, and recover cleanly from failures.
Turn ambitious AI prototypes into dependable products used in real customer workflows.
Work closely with product, AI, research, and platform engineers to define the interfaces between AI capabilities, execution environments, and production services.
Design the execution model for new AI capabilities, build orchestration services for autonomous workflows, improve the scheduling and isolation of distributed workloads, or create APIs that simplify complex runtime capabilities for other engineers.

Requirements

What you’ll need

4+ years of software engineering experience in backend systems, distributed systems, developer platforms, production infrastructure, or a related area.
Strong backend engineering fundamentals, including API design, data modeling, concurrency, debugging, and testing.
Experience designing and operating production services where reliability, observability, and maintainability matter.
Experience reasoning about distributed state and failure modes, including retries, queues, leases, scheduling, idempotency, and long-running workflows.
Practical experience with containers and Kubernetes-backed systems, including workload lifecycle, networking, resource limits, and production debugging.
Experience with production data systems such as Postgres, Redis or Valkey, and object storage.
Experience building orchestration systems, workflow engines, job schedulers, sandboxes, developer platforms, or distributed execution systems.
A track record of designing APIs and abstractions that other engineers can use confidently.
Pragmatic judgment in fast-moving environments: you know when to improve an abstraction, simplify it, or ship the straightforward version.
A strong sense of ownership for how your software behaves in production and how effectively others can use it.

Benefits

Comp & perks

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