Top Tech Jobs & Startup Jobs

Own the technical sales cycle for Exa’s API in India, including customer discovery, solution design, demos, prototypes, POCs, technical evaluations, and objection handling. Partner with account executives, support expansion opportunities, advise customers on AI use cases, feed market insights to product and engineering, and develop regional playbooks. The role also supports onboarding and early implementations while representing Exa at technical events.

Own the full sales cycle for Exa’s AI search product, including prospecting, product demonstrations, customer strategy, contract negotiation, and closing. The role involves building the London go-to-market office, developing high-value customer relationships, collaborating with SDRs, maintaining pipeline momentum, meeting sales targets, and driving revenue growth in a fast-moving startup environment.

Build and maintain large-scale systems to extract, connect, retrieve, and reason over web knowledge. Implement petabyte-scale data pipelines, optimize for correctness/reliability/scale, and improve data quality to power factual QA and search.

Own the design and implementation of a high-scale query engine for hundreds of billions of claims. Responsibilities include storage layout, indexing, query planning, optimization, distributed retrieval across graph, vector, full-text, time-series, and geospatial backends, consistency, latency optimization, and correctness evaluation. The role requires deep distributed database or search infrastructure experience and strong proficiency in Go, Rust, or C++.

Own strategy, roadmap, metrics, and execution for products extending Exa’s search API. Partner directly with AI startups and enterprises to identify needs, unblock integrations, and turn customer pain points into scalable capabilities. Collaborate with engineering, marketing, sales, and field teams on launches, pricing, documentation, enablement, and adoption. Define success criteria across quality, coverage, cost, and speed while driving developer adoption and business outcomes.

Own the quality and completeness of Exa’s evaluation data for search models. Define evaluation metrics and success criteria, build localized feedback signals, acquire and manage external data vendors, and collaborate with ML researchers, data engineers, infrastructure engineers, product, and GTM teams to improve search model performance.

Leads Exa’s EMEA marketing strategy, budget, market prioritization, pipeline generation, sales alignment, product-led growth, developer programs, localized positioning, agencies, and team expansion. The role owns regional pipeline and revenue outcomes across the UK, Europe, Middle East, and Africa, combining enterprise account-based marketing with developer-focused campaigns, events, partnerships, and automated AI-enabled workflows.

Leads Exa’s Asia Pacific and Japan marketing strategy, budget, pipeline generation, go-to-market motions, developer marketing, account-based programs, sales partnership, localization, and regional events. The role manages agencies and partners, hires the APJ marketing team, and uses automation, campaign data, and pipeline metrics to prioritize markets and investments. Based in Sydney, it requires regular APJ travel and periodic trips to San Francisco.

Own the machine-learning signals and decisions governing web crawling and indexing at massive scale. Develop classifiers, rankers, and calibrated models to assess page quality, credibility, freshness, parsing success, duplicate content, and indexing value. Define ground truth for ambiguous problems, validate measurable search improvements, and collaborate across crawling, indexing, and retrieval teams to improve the quality and coverage of search results.

Develop large-scale machine learning systems for web content understanding and search quality. Responsibilities include parsing web pages, classifying content, extracting metadata, assessing quality and credibility, detecting misinformation and AI-generated content, deduplicating documents, designing supervision for unlabeled problems, and building efficient models that operate across the web in every language and format.