Senior Software Engineer

About the role

Mutiny is building the self-improving AI infrastructure layer that allows GTM teams to execute faster and close more revenue, and this role is central to that mission. You will own the core agent surfaces that power the Campaign Builder and Agent experiences, ensuring that non-deterministic models feel deterministic at the point of use. This position requires deep end-to-end responsibility spanning frontend, backend, prompts, evals, and guardrails across thousands of customer accounts. You will directly partner with product, design, and founders to define the agent-first GTM platform experience and set the architectural vision for the company. The role operates in person in New York City, five days a week, with a weekly shipping cadence that demands consistent execution. Your decisions on architecture, evals, and guardrails will compound across the entire customer base and shape how the platform evolves.

Key facts

What you'll do

• Architect and ship the core agent surfaces end-to-end, owning the Campaign Builder and Agent experiences across frontend, backend, prompts, evals, and guardrails.
• Make non-deterministic LLMs feel deterministic at the surface by building robust retries, fallbacks, and orchestration that prevent customers from ever seeing failure modes.
• Define and own evals and guardrails that measure quality, catch regressions, and maintain brand and tone consistency across thousands of customer accounts.
• Obsess over speed and feel, reducing latency and shortening the loop between intent and output, while leveraging coding agents and agent networks to ship faster than felt possible last year.
• Sit with product and design to prototype the hardest interactions yourself, actively shaping product definition rather than waiting for specifications to be handed down.
• Write clear design documents that make the room smarter, explaining nuanced technical decisions in writing and in real-time discussions with stakeholders.
• Raise the bar for the engineering organization by mentoring junior engineers, driving sharp code review, and being direct when technical or product tradeoffs require correction.
• Own the reliability and scalability of agent workflows, ensuring that the platform maintains high performance and stability as customer usage grows exponentially.
• Explore and adopt emerging agent frameworks and coding agents, distinguishing research-paper hype from abstractions that hold up at scale and contribute to sustainable velocity.
• Collaborate closely with founders and leadership to align technical execution with the strategic vision of building a generational AI GTM company backed by top-tier investors.
• Build tools and infrastructure that enable sales and marketing teams to move faster, personalizing assets in minutes while maintaining tight feedback loops from real revenue motion.
• Drive the evolution of the agent-first platform by anticipating future needs and designing extensible systems that reduce friction for downstream teams and customers.

Requirements

• Full-stack engineer by instinct, comfortable navigating from prompt design through backend services to frontend user interactions without handoffs.
• Experienced shipping AI applications in production, with proven work in RAG, evals, agent frameworks, and coding agents on live systems.
• Strong fundamentals in at least a backend language such as Python, TypeScript, Kotlin, or Ruby, with a track record of writing maintainable and readable code.
• Clear written and verbal communication skills, capable of explaining complex technical tradeoffs in real-time and through detailed design documents.
• Builder mentality, preferring to prototype difficult interactions yourself rather than waiting for perfect specifications or consensus.
• High ownership mindset, willing to make architectural decisions that compound across customer accounts and define the long-term direction of the platform.
• Commitment to raising the standard of engineering quality through rigorous code review, generous mentorship of junior engineers, and directness when issues arise.
• Comfort working in a fast-moving environment where ambiguity is common and decisions must be made with incomplete information.
• Demonstrated ability to build reliable systems on top of LLMs, balancing innovation with the practical needs of stability and performance in customer-facing products.