🧠 About Feather

Feather is building AI agents that do real work for enterprises.

Not chatbots. Not IVR. Not copilots.

Autonomous agents that can reason, take actions, communicate across channels (voice, text, email), and complete end-to-end business workflows.

We operate at the intersection of LLM reasoning, real-time communication, and production system orchestration — enabling companies to deploy AI employees across sales, support, operations, and collections.

Feather is building the infrastructure and runtime layer that makes autonomous agents production-ready across communication channels.

We’re backed by leading investors and already at $1M+ ARR, scaling quickly into enterprise deployments.

🔧 What You’ll Do

Agent Runtime & Cognition Systems

Design and build the core runtime that powers autonomous AI agents
Architect systems for reasoning loops, planning, tool use, and memory
Enable agents to execute multi-step workflows across business systems

Multi-Channel Communication Infrastructure

Build systems enabling agents to operate across voice, SMS, chat, and email
Develop real-time conversation pipelines and turn management
Handle interruptions, context switching, and long-running dialogues

Orchestration & Workflow Execution

Develop agent orchestration layers for async and long-lived tasks
Build DAG/workflow systems coordinating agent decisions and actions
Enable outcome-based automation (not just conversations)

Applied LLM Systems

Integrate frontier models into production agent systems
Build prompt pipelines, evaluation harnesses, and guardrails
Design reliability layers: fallbacks, retries, human handoffs

Distributed Systems at Scale

Architect event-driven systems handling millions of agent actions
Build job queues, schedulers, and execution pipelines
Optimize latency, throughput, and infrastructure cost

🧩 What We’re Looking For

Core Engineering Depth

3–7 years building scalable backend or distributed systems
Strong experience in Python or TypeScript
Deep understanding of async processing and event-driven systems
Experience designing production APIs and service architectures

Agent / AI Systems Exposure

Experience working with LLM APIs in production environments
Familiarity with agent frameworks, reasoning systems, or tool use
Built systems where AI drives real user or business outcomes

Systems Ownership Mindset

Comfortable owning infra end-to-end
Strong debugging and performance optimization skills
Product-minded — you think in workflows, not endpoints

🌟 Bonus Points

Built agent tooling (memory, planning, tool execution)
Experience with workflow engines or orchestration systems
Familiarity with real-time communication infra
Experience with RAG, knowledge bases, or retrieval systems
Exposure to eval frameworks and agent reliability testing
Worked on customer ops, sales, or support automation

🏗️ Tech Stack

LLMs: OpenAI + frontier / open-weight models
Agent Systems: Custom runtimes + orchestration frameworks
Communication: Voice, SMS, chat, email infrastructure
Backend: Python, TypeScript
Infra: AWS, Kubernetes, Postgres, Redis
Observability: Prometheus, Grafana, tracing
Workflows: Queue + DAG orchestration systems

💼 What We Offer

Competitive salary + founding equity
Direct ownership of core platform architecture
Work on frontier agent infrastructure problems
Build AI systems deployed in real enterprise workflows
Fast shipping velocity with technical founders

🎯 Who This Role Is For

Engineers who want to:

Build AI agents that take actions — not just generate text
Work on reasoning systems, orchestration, and autonomy
Design infrastructure for AI employees
Shape the foundation of an emerging category

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