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Staff AI Platform Engineer

AlphaSense
On-site
San Francisco, CA, United States
Full-time
$203,000 - $304,000

About AlphaSense

The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content.

The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us!

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.

Qualifications

7+ 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.).

Responsibilities

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.
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