Senior Engineering Manager, Agent Context

Навыки

• Elasticsearch
• Лидерство
• LLM
• Machine Learning
• Ответственность за результат
• RAG
• Роадмап

О компании и продукте

• Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.
• We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law.
• Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Задачи

• Own the technical direction and delivery of Asana's retrieval stack end to end: lexical and semantic search, dense embedding generation and backfill at scale, chunking and ranking strategies, and RAG comprehensiveness across the work graph
• Build and operate the evaluation infrastructure that makes retrieval quality measurable recall/precision benchmarks, offline and online evals, and comparative testing across retrieval backends - so quality decisions are made with data, not vibes
• Drive the cost, performance, and quality tradeoffs that define this space: when semantic search earns its infrastructure cost over lexical, how to hit latency targets without sacrificing recall, and how retrieval improvements compound into cheaper, faster downstream LLM calls
• Set and enforce the bar for how other teams at Asana integrate with retrieval: clear ownership of embedding decisions, rollout guidance, metrics to watch, and a platform posture that says no to unjustified infrastructure spend
• Hire, grow, and retain a team of strong senior engineers in NYC, and lead effectively across three time zones with deliberate async communication practices
• Partner with your PM counterpart to translate a multi-year platform thesis into a sequenced roadmap, and represent the team's technical strategy to engineering and product leadership

Требования

• 8+ years of software engineering experience with 3+ years managing engineers, including senior engineers, on infrastructure or ML systems teams
• You've hired, coached, grown, and when necessary exited engineers and your former reports would work for you again
• You have shipped and operated production search, retrieval, or ML-serving systems at meaningful scale
• You can speak concretely about systems you've run: the index architecture, the embedding models, the latency budgets, the incidents, and what you'd do differently
• Deep working knowledge of the modern retrieval stack inverted indexes and BM25, vector search and embedding models, hybrid retrieval, chunking strategies, re-ranking and strong opinions about when each is worth its cost
• You should be able to argue both sides of "semantic search everywhere" and tell us where you actually land
• You've built or heavily used evaluation systems for ML/AI quality: golden datasets, recall/precision metrics, LLM-as-judge, online experimentation
• You believe unmeasured quality claims are noise
• You're technically credible enough to review a design doc for an embedding backfill or an OpenSearch mapping change and catch the problem the team missed
• You don't need to write the code, but engineers should leave design reviews with you sharper than they arrived
• You've led distributed teams across time zones and know that it runs on written communication. You write clearly, decisively, and often
• Experience with LLM-powered products, agent systems, or RAG pipelines in production is strongly preferred
• Experience scaling a platform team that serves internal customers is a plus

Условия

• Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission
• We believe that compensation should be reflective of the value you create relative to the market value of your role
• To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit
• For this role, the estimated base salary range is between $264,000 - $300,000
• The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process
• The listed range above is a guideline, and the base salary range for this role may be modified
• In addition to base salary, your compensation package may include additional components such as equity and benefits
• We strive to provide equitable and competitive benefits packages that support our employees worldwide and include
• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences

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