About Poggio
Poggio is bringing the power of generative AI to sales teams. The Poggio platform leverages the cutting edge of AI to automate large portions of the enterprise sales workflow, including pipeline generation, account planning, account research and meeting prep, deal reviews, territory planning, and QBRs. Poggio amplifies the capabilities of salespeople so they can spend more time building relationships with their customers, and less time on non revenue generating activities.
We're reimagining the day-to-day of sales workflow and changing the way that sellers build relationships and earn trust with their customers. We're developing our product alongside the best enterprise sales teams on the planet, and are deployed in production powering their day to day sales motions.
We’re supported in our mission by world-class investors from Accel and Spark Capital.
Our team is remote first, with opportunities for occasional in-person collaboration. We have a slight preference for SF / NYC, but we’re flexible on location — our top priority is finding the perfect fit.
AI engineering
Large language models enable many of Poggio's core product features, therefore AI engineering is tightly coupled with ongoing product initiatives. We are looking for an experienced and ambitious software engineer to help us extend and scale the foundations of our AI system in order to power new user capabilities and provide the best possible AI user experience for our customers.
We're open to multiple levels of experience for this role. More than anything, we're looking for people who are a great fit for Poggio.
Required skills
- Analytical thinking, creative problem solving, product orientation, and strong collaboration
- Track record of partnering successfully with cross-functional stakeholders
- Expert level proficiency using multiple programming languages
- Relevant mathematical foundations (probability, stats, modeling, optimization, logic, discrete math)
- Knowledge and experience using unsupervised, supervised, in-context, and reinforcement learning techniques
- Experience implementing LLM observability and system performance evaluations
- Experience building and optimizing information retrieval systems
- Nuanced understanding of the capabilities and limitations of large language models
- Knowledge of data processing, retention, and privacy policies
Role expectations
- Exhibit a strong desire to win as a team
- Be extremely curious, open-minded, and action oriented
- Collaborate with engineers and designers on delivering AI capabilities up and down the stack in service of our product and users
- Systematically work to improve AI system performance metrics, and help design new metrics aligned with our product initiatives
- Explore, champion, and apply emerging techniques from AI systems research
- Wear a lot of hats — expect to touch everything: infra, data pipelines, multi-modal indexing, retrieval, agents, tools, observability, evaluations, and more
Benefits
- Unlimited, Flexible PTO
- Remote-first with option to work in co-working spaces or our SF HQ
- At least biannual off-sites to meet with the team
- Health care plan (Medical, Dental, Vision)
- 401k plan with employer matching
- Annual Wellness Stipend: $1200 per year for your choice of wellness-related expenses such as gym memberships, massages, fitness equipment, ski pas, etc.
Compensation
Competitive salary and equity according to leveling assessment, calibrated to Tier-1 U.S. market data.
Our Interview Process
We do 5 interviews, then pay you to do a work trial which is close to what you may do for your day-to-day work.
- Application (You are here): Our talent team will review your application to see how your skills and experience align with our needs.
- Recruiter Meeting (30 min video call): Our goal is to explore your motivations to join our team, learn why you’d be a great fit, and answer questions about us.
- Manager Meeting (45 min video call): You'll meet the hiring manager who will evaluate skills needed to be successful in your role.
- Technical Interview (60 min video call): You'll meet someone from the engineering team who will evaluate your technical skills. This is a live coding interview.
- Cross-functional Interview (45 min video call): You will meet with someone from outside of engineering to discuss your past experience working in cross functional product development teams.
- System Design Interview (60 min video call): You'll meet someone from the engineering team who will evaluate your system design skills.
- Paid Work Trial (All day): You will spend a day (remotely or in-person depending on location) working on a task related to your role, meeting the team, and seeing what a realistic day is like working at Poggio.