Senior​/Software Engineer, AI Platform

Our client is building one of the largest AI-powered productivity platforms in the world.

Millions of users rely on the platform every day to manage projects, collaborate with teams, organize information, automate workflows, and execute work across their organizations.

The company is making a significant investment in AI and is rapidly evolving from a traditional SaaS platform into an AI-native product experience where assistants, agents, automation, and intelligent workflows become a core part of how work gets done.

This is not an early-stage experiment or innovation lab. These systems are live, customer-facing, and operating at meaningful scale.

The engineering organization moves quickly, values ownership, and expects engineers to build solutions that solve real user problems in production environments.

This is a software engineering role focused on building AI-native products and the systems that power them.

We are looking for engineers who have successfully built and shipped production AI systems, agentic workflows, AI copilots, orchestration layers, and intelligent product experiences that real users rely on every day.

This is not a machine learning research role.

This is not a data science role.

This is not a prompt engineering role.

The ideal candidate is a strong backend or platform engineer who has evolved into building sophisticated AI systems and understands the challenges of operating those systems reliably at scale.

You will help design and build the infrastructure, orchestration frameworks, agent systems, evaluation layers, and platform capabilities that power AI experiences across the product.

• Design and build production AI systems used by millions of users
• Develop agentic workflows that can reason, plan, retrieve context, call tools, and execute multi-step tasks
• Build orchestration layers that coordinate agents, models, tools, memory, and workflows
• Design and evolve AI platform services that support AI-powered product experiences
• Build retrieval and context management systems that improve AI accuracy and effectiveness
• Create evaluation frameworks that measure quality, reliability, and user outcomes
• Optimize AI systems for latency, cost, scalability, and performance
• Improve observability, monitoring, and reliability across AI infrastructure
• Partner with product and engineering teams to bring AI capabilities directly into customer workflows
• Own systems from design through production deployment and ongoing iteration

• 5+ years of professional software engineering experience
• Experience building and shipping production AI-powered products used by real customers
• Experience with agentic systems, AI copilots, orchestration frameworks, tool-calling architectures, or multi-step AI workflows
• Strong systems design and architecture skills
• Experience designing reliable, scalable backend systems
• Strong understanding of APIs, asynchronous processing, distributed systems, and cloud infrastructure
• Experience working with OpenAI, Anthropic, Gemini, or similar LLM providers in production environments
• Ability to operate independently and own complex technical problems from concept through deployment

• Built production AI agents that perform meaningful work rather than simple chat interactions
• Designed systems that manage memory, context, planning, tool usage, and long-running workflows
• Built AI-powered product experiences used by large customer bases
• Developed evaluation, monitoring, and reliability frameworks for AI systems
• Experience balancing latency, cost, reliability, and model quality in production
• Strong product mindset and ability to connect technical decisions to user outcomes

• Experience building multi-agent systems
• Experience with Lang Graph, DSPy, Auto Gen, CrewAI, Semantic Kernel, or similar frameworks
• Experience with retrieval systems, vector databases, and context management
• Experience with AI infrastructure, orchestration platforms, or internal developer tooling
• Experience working in high-growth SaaS environments
• Staff-level engineering experience or scope

• Your background is primarily machine learning research or academic AI
• Your experience is focused on model training rather than software engineering
• Most of your AI work has been experimentation, notebooks, prototypes, or proofs of concept
• You have not owned production AI systems used by customers
• Your experience is primarily prompt engineering without deeper systems ownership
• You prefer research environments over product development and execution

• Competitive Equity Package
• 401(k)
• Health, Dental, and Vision Coverage
• Flexible PTO
• Professional Development Support

AI is becoming a foundational layer of the product. The systems built by this team will directly influence how millions of users retrieve information, automate work, interact with software, and execute complex tasks.

This is an opportunity to help define what AI-native productivity software looks…