Software Engineer

7X Partners; San Francisco (CA); Hybrid; USD 260,000 - 360,000; Full time

Benefits offered by this job

Hybrid work option

Bay Area preferred

Job summary

7X Partners is building the agent layer behind a new generation of creative products in San Francisco. You’ll develop the agent harness, MCP servers, and CLI tooling to power conversations, multi-step planning, and integration with multiple model vendors.

You will ship frontend experiences in React/Next.js and help define how frontier models are orchestrated, with high ownership in a small, founder-led team. Hybrid Bay Area work is available.

Qualifications

• 2+ years of full-stack engineering experience shipping production software.
• Hands-on experience building LLM-powered agents with real users.
• Familiarity with agent harness concepts: tool use, memory management, multi-step planning, sub-agent orchestration.
• Solid data modeling and schema design for real product use cases.
• Strong AI-assisted coding practice using Claude Code, Codex, or Cursor.
• Product sense for trustworthy and delightful agent experiences.
• Clear communication to explain agent behavior and trade-offs.

Responsibilities

• Build and extend the agent harness powering conversational and autonomous creative workflows.
• Develop MCP servers and CLI tooling to connect agents to services and model vendors.
• Author reusable Agent Skills and structured workflows for complex tasks.
• Contribute to evaluation frameworks and observability to catch regressions.
• Ship production frontend experiences (React/Next.js) for agent-driven products.
• Make pragmatic trade-offs between speed, correctness, and scalability and communicate them clearly.
• Partner with product, design, and GTM to translate user needs into technical solutions.
• Track the fast-moving agent ecosystem and bring best practices into our stack.

Skills

Full-stack engineering

LLM-powered agents

Agent harness concepts

Data modeling

AI-assisted coding

Product sense

Clear communication

Tools

Claude Code

Codex

Cursor

LangGraph

Claude Agent SDK

Job description

We're hiring engineers to build the agent layer behind the next generation of creative products, starting with Director which lets anyone "vibe direct" a multi-minute cinematic video by chatting with AI. You'll be building the agent infrastructure that pushes experiences like this further: longer-horizon planning, tool use across multiple model vendors, memory across sessions, and the harness that keeps all of it reliable in production.

This isn't a research role it's a product-and-systems role. You'll build on and extend the agent harness (tool use, context management, multi-step planning, evaluation), develop the MCP servers and CLI tooling around it, and ship the frontend experiences that make all of it feel effortless rather than technical. You'll work closely with the founders, the agent team, and design to turn "what should this agent be able to do" into a system that actually does it reliably, at scale.

• Ground floor of a new category help define what "agent" means for creative work, the way Director redefined what "directing" means for video.
• Small team, massive surface area engineers own real systems end to end, not slices.
• Real scale, real stakes your agents run for millions of creators, and what you ship shows up in the product within days.
• Founder-led engineering culture both founders are technical and deeply involved in product and architecture.
• AI-native product you'll help decide how frontier models get orchestrated and exposed as experiences that feel effortless rather than technical.
• High ownership, low process we value judgment, clarity, and speed over bureaucracy.

What You’ll Do

• Build and extend the agent harness that powers of conversational and autonomous creative workflows: tool use, context/memory management, multi-step planning, and sub-agent orchestration
• Build and maintain MCP servers and CLI-based agent tooling that connect our agents to internal services, external model vendors, and creative asset pipelines
• Author reusable Agent Skills and structured workflows that let agents reliably handle complex, multi-step creative tasks scene planning, storyboarding, asset generation, revision loops
• Contribute to evaluation frameworks and observability so the team knows when an agent is working well, and can catch regressions before users do
• Ship polished, production frontend experiences (React/Next.js) for agent-driven products, end to end
• Make pragmatic trade-offs between speed, correctness, and scalability and communicate them clearly
• Partner closely with product, design, and GTM to translate user needs into technical solutions
• Track the fast-moving agent ecosystem (MCP, Agent Skills, orchestration frameworks) and bring the best of it into our stack

Core Requirements

• 2+ years of full-stack engineering experience shipping production software
• Hands-on experience building LLM-powered agents or applications that have reached real users not just prototypes or demos
• Working familiarity with agent harness concepts: tool use, context/memory management, multi-step planning, or sub-agent orchestration
• Solid data modelling and schema design skills for real product use cases
• A strong AI-assisted coding practice you use tools like Claude Code, Codex, or Cursor as a core part of how you build, and have real opinions about what makes them work well
• Product sense you think about what makes an agent experience feel trustworthy and delightful, not just functional
• Clear communication you can explain agent behaviour and technical trade-offs to teammates who aren't engineers

Nice to Have

• Experience authoring reusable Agent Skills or structured agent workflows
• Practical experience building MCP servers or CLI tooling for agents
• Exposure to agent orchestration frameworks (Claude Agent SDK, LangGraph, or similar) or LLM evaluation / observability tooling
• Hands-on experience with image / video generation models
• Startup experience, or having built something 0 to 1 (side projects count)
• $300k+ total compensation including base salary, bonus, equity
• Equity - meaningful ownership in what you build
• High autonomy, high growth environment
• Bay Area preferred (hybrid available)

What Success Looks Like in 3–6 Months

• You’ve shipped a production agent workflow inside our ecosystem, and real users are running it
• You’ve meaningfully improved a piece of the harness, a set of Agent Skills, or the eval loop and can point to the metric that moved