Staff Software Engineer (FullStack)

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

Join us as a Full Stack Staff Engineer to lead the evolution of the AlphaSense Application Portfolio through robust architecture and cutting-edge AI integration. This role is designed for a seasoned engineer who thrives on solving massive-scale frontend challenges and building performant, customer-focused systems. You will act as a strategic lead—researching and architecting solutions for complex frontends, while fostering a culture of technical excellence across the team. If you are looking to combine hands-on AI innovation with high-impact organizational leadership, this role is for you.

What You’ll Do

• Serve as the Architectural Anchor for integrating AI into the product fabric. You will research, prototype, and deploy cutting-edge solutions using LLMs and the latest frontend technologies, ensuring these models are not just theoretical but are seamlessly integrated into high-performance, user-facing applications.
• Design the frontend architecture that serves as the gateway to our AI platform. You will build robust, scalable interfaces capable of rendering insights from millions of documents with sub-second latency. By bridging the gap between complex AI services and the end-user, you will ensure that massive-scale data is transformed into performant, intuitive, and highly responsive web applications.
• Partner with cross-functional, distributed teams to evaluate and adopt emerging technologies, while leading the seamless integration and optimization of intelligent features and high-impact workflows across the platform
• Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are

Core Qualifications

• 8+ years of experience building complex, data-intensive full-stack systems, with 5+ years specifically scaling production-grade services using Node.js, GraphQL, and modern JavaScript/TypeScript ecosystems.
• Deep expertise in React and TypeScript; a proven ability to codify performance best practices, navigate complex architectural trade-offs, and drive code-level improvements.
• Proven success in designing large-scale asynchronous systems using streaming, queuing, and caching strategies, supported by robust observability (logging, metrics, tracing).
• Strong proficiency with SQL/NoSQL (e.g., DynamoDB, Elasticsearch, Vespa) and cloud-native development within AWS or GCP.
• Working knowledge of Python or Java/Spring.
• Passion for AI-assisted development (e.g., Cursor, Claude)
• Exceptional communicator able to articulate complex technical concepts and influence engineering direction across multiple teams without direct authority.
• Prior experience at global technology companies or high-growth product organizations with a high-bar engineering culture.

Nice to have

• Proficient in modern DevOps/MLOps, including CI/CD, IaC, and automated testing frameworks.
• Hands-on experience with Docker and Kubernetes for containerized application delivery.
• Practical experience deploying LLM applications, agentic frameworks, or scalable AI infrastructure.