About Mixpanel
Mixpanel turns data clarity into innovation. Trusted by more than 29,000 companies, including Workday, Pinterest, LG, and Rakuten Viber, Mixpanel’s AI-first digital analytics help teams accelerate adoption, improve retention, and ship with confidence. Powering this is an industry-leading platform that combines product and web analytics, session replay, experimentation, feature flags, and metric trees. Mixpanel delivers insights that customers trust. Visit mixpanel.com to learn more.
About the Team
The AI Platform team is a newly formed team at the center of Mixpanel's AI-first analytics vision. With a greenfield charter, we're building the infrastructure that accelerates and transforms AI product development at Mixpanel, both internally and for our customers.
We provide the tools to improve AI products, enabling internal teams and customer agents to build things that were previously unimaginable. We build shared infrastructure that is essential for developing AI features with confidence and speed, and that gives every agent the tools, context, and quality guarantees to act autonomously on behalf of users.
Some examples of what we are building:
- Agent Optimization Framework: A system that optimizes AI products for quality, speed, and cost, using metrics from production and evals, given the context of the invocation.
- AI Agent Integrations and Accessibility: Products and tools that bring the power of Mixpanel to wherever it is most effective for our customers, including a Mixpanel slackbot, MCP, and a public skills library.
- AI Engine: Services that centralize core AI and LLM functionality at Mixpanel in order to accelerate AI development, compound the value of AI efforts, and provide customers with a consistent experience.
Role Overview
We are looking for an experienced and driven Senior Software Engineer to join our AI Platform team. You will be responsible for building the scalable, secure, and reliable infrastructure that accelerates AI agent development. You will be a leader and key contributor in a small, fast paced, newly formed team with a mandate to empower AI development across the company.
Responsibilities
- Platform Architecture: Design and develop the core backend services, APIs, and microservices that enable product teams to easily and securely leverage AI models.
- Agent Orchestration: Build scalable frameworks and tools to support multi-step agent workflows, including task decomposition, tool invocation, and persistent memory.
- Evaluation & Reliability: Build robust evaluation systems to continuously measure reasoning quality, hallucination rates, and task success.
- Operational Excellence: Architect high-performance serving infrastructure with strict guarantees around latency, throughput, cost-efficiency, and error handling.
- Observability & MLOps: Ensure comprehensive monitoring, structured logging, and distributed tracing across all deployed AI models.
- Collaboration: Partner with designers, product managers, and other engineers to build self-serve infrastructure that transforms our AI development cycle.
- Leadership: Advocate for software engineering best practices, conduct thorough design and code reviews, and mentor junior engineers.
We're Looking For Someone Who Has
- Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience
- 5+ years of professional software engineering experience
- Strong full-stack fundamentals: you're comfortable working across frontend, backend, and data layers
- Excellent debugging and technical investigation skills
- Strong technical communication, ideally with experience collaborating in an asynchronous remote environment
- Ability to move fast and iterate in ambiguous environments: you take ownership and focus on delivering value to users
- Hands on experience integrating and orchestrating LLMs and agents
- Experience building AI native systems, including iteratively improving and scaling them in production
- Familiarity with techniques used to optimize AI agents: eval frameworks, agent tooling, vector search engines, context engineering, and prompt engineering.
- A desire to be on the forefront of leveraging AI to drive product improvement, observability and product analytics at scale.
Compensation