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AlphaSense is a market intelligence platform trusted by over 6,000 enterprise customers, including a majority of the S&P 500. The company uses AI-driven search and analytics to help sophisticated organizations remove uncertainty from decision-making, processing content including equity research, company filings, event transcripts, expert calls, news, and trade journals.
You will join as a Staff Software Engineer on the content processing and intelligence team. This role operates at the intersection of technical depth and organizational influence. You will own technical direction for your area, make build-vs-buy decisions, define architecture, and partner with product leadership on the technical roadmap.
Key responsibilities include:
- Setting technical direction and owning the technical roadmap for your area
- Taking ambiguous business problems and translating them into concrete technical strategies
- Designing and delivering production-grade systems: scalable data pipelines, robust backend services, and high-performance solutions serving real users at scale
- Leveraging AI tools (Claude Code, Cursor, Copilot) as part of your development workflow
- Evaluating and integrating AI/ML capabilities (LLMs, embeddings, classification models) into production systems
- Driving cross-team technical initiatives and influencing engineers you don't formally manage
- Owning systems end-to-end: from requirements through release to production monitoring, SLOs/SLIs, and continuous reliability improvement
- Raising the engineering bar through code reviews, mentorship, technical documentation, and modeling expected standards
The team designs and operates large-scale systems that ingest, process, and enrich diverse content types. You will build and own backend services and high-throughput data pipelines that transform raw content into structured, searchable intelligence.
Interview process includes a hands-on session in a real development environment (not whiteboard). You'll work on a realistic, messy codebase with AI tools pre-configured. Evaluation focuses on how you navigate unfamiliar code, leverage AI tools critically, decompose problems, and communicate trade-offs.
REQUIREMENTS:
- Strong proficiency in Python (primary backend language); comfortable working across languages with production code shipped in at least two
- Designed and owned production systems serving real users at scale—not just contributed, but made consequential architectural decisions and lived with outcomes
- Led cross-team technical initiatives without formal authority (migrations, platform changes, architectural shifts requiring multi-team alignment)
- Strong system design instincts: think in terms of failure modes, data flow, scalability, operational cost; design for systems you'll maintain, not just ship
- Deep DevOps and operational experience: Kubernetes, cloud infrastructure (AWS/Azure/GCP), CI/CD, observability; don't throw code over the wall
- Track record mentoring engineers and raising team standards through pairing, reviews, RFCs, and leading by example
GOOD TO HAVE:
- Experience leading large-scale migrations or platform rewrites
- Hands-on production experience with AI/ML: LLMs, BERT, NLP pipelines, document understanding systems
- Contributed to or driven engineering-wide standards, practices, or tooling
- Experience with content processing, enrichment, or search systems at scale
- Familiarity with Java (parts of their stack)
- Experience with GitOps, ArgoCD, or Infrastructure as Code
- Active practitioner of AI-assisted development (AIDLC); uses AI tools daily in engineering workflow
