Senior Infrastructure Engineer, AI Platform

About Manifest

Manifest OS is an AI-native company on a mission to replace the billable hour and make legal services more accessible for American businesses and consumers. We power the next generation of AI-native law firms with one unified global brand, a proprietary technology platform, and a centralized back office — enabling lawyers to eliminate the administrative burden and focus on delivering exceptional outcomes for their clients. Backed by leading venture investors, Manifest O.S. is scaling rapidly.

About the team

Our AI Platform team builds the foundational systems powering AI features across our entire product. We're the engine room that makes it possible for product engineers to ship LLM-powered features without drowning in the operational complexity of model management, cost optimization, and reliability concerns. The team collaborates closely with product engineering, data science, and platform teams to ensure our AI infrastructure scales seamlessly with business needs.

Ideal experience

You have 6-9 years of infrastructure engineering experience with a proven track record of building and operating distributed systems at production scale. You've lived through the challenges of high-throughput, low-latency systems and understand the tradeoffs between consistency, availability, and partition tolerance. Your background likely includes experience with service meshes, API gateways, observability platforms, or developer tooling — areas where reliability and developer experience are equally critical.

While you may not have extensive AI/ML experience, you're comfortable diving into unfamiliar technical domains and have the systems thinking to tackle the unique challenges of LLM operations. You understand that AI infrastructure is fundamentally different from traditional backend systems — dealing with non-deterministic outputs, variable latencies, cost optimization across multiple vendors, and the rapid pace of model evolution. You've likely worked on platform teams before and understand that your success is measured by enabling other engineers to ship faster and more reliably.

You're the type of engineer who thinks in abstractions and APIs. When faced with complex operational challenges, your instinct is to build systems that solve the problem once for everyone rather than letting each team solve it individually. You have strong opinions about developer experience and can balance the competing demands of flexibility, simplicity, and performance when designing platform services.

What You'll Own

This role sits at the intersection of traditional infrastructure engineering and the emerging world of LLM operations. You'll be building the critical platform that abstracts away the complexity of AI/ML systems for our product engineers, making it trivial for them to integrate sophisticated AI capabilities into user-facing features. Think of yourself as the architect of our AI nervous system — designing the model gateway that routes requests intelligently, building observability systems that give us visibility into black-box model behavior, and creating developer tools that make prompt engineering feel like traditional software development.

The impact of this role extends far beyond infrastructure. Every AI feature our company ships will rely on the systems you build. You'll be solving fascinating technical challenges: how do you route requests between different model providers to optimize for cost and latency? How do you build reliable observability for non-deterministic systems? How do you create developer experiences that make working with LLMs feel predictable and debuggable? This is greenfield infrastructure work with immediate business impact.

This is an opportunity to define the future of AI platform engineering at our company. You'll have significant autonomy to choose technologies, design architectures, and set engineering standards for a rapidly evolving domain. The work requires both deep technical expertise and strong product intuition — your customers are fellow engineers, and their productivity depends on the abstractions and tools you create.

This for you if

You thrive in ambiguous, rapidly evolving technical domains and get energized by building systems that other engineers depend on. You have strong opinions about API design and developer experience, but you're also pragmatic about making tradeoffs to ship quickly. You're comfortable being one of the first engineers to tackle a problem space and can balance moving fast with building systems that will scale. You enjoy the detective work of debugging complex distributed systems and aren't frustrated by the inherent unpredictability of working with LLMs.

You're motivated by enabling others and understand that platform engineering success is measured by the productivity and happiness of your internal customers. You communicate well with both technical and non-technical stakeholders and can translate complex infrastructure decisions into business impact. You're comfortable with the responsibility of owning critical infrastructure and take pride in building systems that work reliably even when everything around them is changing rapidly.

Not for you if

If you prefer working on well-defined problems with established best practices, this role will likely frustrate you. The AI infrastructure space is evolving rapidly, and you'll need to be comfortable making architectural decisions without clear precedents. If you're someone who needs detailed requirements and specifications before starting work, or if you prefer working on features that directly impact end users rather than enabling other engineers, this probably isn't the right opportunity. This role requires a high tolerance for ambiguity and the ability to iterate quickly based on feedback from internal customers.