Staff AI Platform Engineer
AlphaSense is seeking an experienced engineering leader to transform how we build and operate AI-powered systems at scale. You'll join a team of brilliant engineers who've built cutting-edge AI applications, and your mission will be to bring world-class engineering practices that ensure these innovations run reliably for our enterprise customers.
This is a unique opportunity for a seasoned engineer who thrives on building robust platforms, mentoring talented teams, and establishing engineering excellence. You'll have significant autonomy to shape our technical architecture while working with frontier AI models and agentic systems that power market intelligence for the world's leading companies.
Key responsibilities include designing and implementing distributed systems that power AI agents processing thousands of requests per hour, ensuring reliability, performance, and cost-efficiency. You'll establish comprehensive testing strategies, observability systems, and CI/CD pipelines that catch issues before customers do. Additionally, you'll mentor a team of smart, motivated engineers, sharing your experience in building production systems that don't break at 3 AM. You'll own the technical roadmap for our AI platform, making architectural decisions that will shape our systems for years to come, and collaborate with ML engineers and researchers to productionize cutting-edge AI capabilities while maintaining system stability.
The ideal candidate has 7+ years of experience building and operating distributed systems in production, with a track record of improving system reliability. Deep expertise in modern engineering practices such as microservices, containerization (Kubernetes), and infrastructure as code is essential. Experience leading technical initiatives and mentoring engineering teams, strong coding skills with the ability to work across the stack, and excellence in debugging production issues and implementing comprehensive observability are also required. A history of making pragmatic trade-offs between perfect and shipped is highly valued.
Preferred qualifications include experience with LLM applications, agent frameworks, or AI/ML infrastructure, familiarity with prompt engineering, RAG patterns, vector databases, and a background at high-growth companies or modern engineering cultures. Experience with multi-model AI systems (OpenAI, Anthropic, Google, etc.) is also desirable.
Within your first year, you'll transform how we build and operate software. You'll reduce incidents, establish testing and observability standards that become part of our DNA, and build platforms that enable other engineers to ship faster and safer. Most importantly, you'll elevate an entire team of engineers, sharing the expertise that only comes from years of building systems at scale.