Staff Engineer, AI Product
About the Role
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.
What You'll Do
Architect for Scale: Design and implement distributed systems that power AI agents processing thousands of requests per hour, ensuring reliability, performance, and cost-efficiency
Build Engineering Excellence: Establish comprehensive testing strategies, observability systems, and CI/CD pipelines that catch issues before customers do
Lead Through Expertise: Mentor a team of smart, motivated engineers, sharing your experience in building production systems that don't break at 3 AM
Drive Platform Evolution: Own the technical roadmap for our AI platform, making architectural decisions that will shape our systems for years to come
Bridge AI and Engineering: Collaborate with ML engineers and researchers to productionize cutting-edge AI capabilities while maintaining system stability
What We're Looking For
Required:
8+ years building and operating distributed systems in production
Track record of improving system reliability (taking services from frequent outages to 99.9%+ uptime)
Deep expertise in modern engineering practices: microservices, containerization (Kubernetes), infrastructure as code
Experience leading technical initiatives and mentoring engineering teams
Strong coding skills with ability to work across the stack
Excellence in debugging production issues and implementing comprehensive observability
History of making pragmatic trade-offs between perfect and shipped
Preferred:
Experience with LLM applications, agent frameworks, or AI/ML infrastructure
Familiarity with prompt engineering, RAG patterns, vector databases
Background at high-growth companies or modern engineering cultures
Experience with multi-model AI systems (OpenAI, Anthropic, Google, etc.)
Impact You'll Have
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.