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About People.ai
People.ai accelerates enterprise growth through the power of AI. With the industry’s only Revenue Intelligence System, People.ai frees all customer-facing teams, including sales, marketing, and customer success, from manual data entry by automatically capturing all contact and customer activity data, dynamically updating CRM and other systems of record, and providing actionable intelligence across management tools to realize the full selling capacity of the enterprise. Some of the world’s best brands are leveraging People.ai to transform their business, including Lyft, New Relic, Okta, Tanium, and Zoom.
At People.ai, we believe that people enrich the world around them in countless ways. We believe that the more time they spend applying their creativity, resourcefulness and critical thinking to activities that matter most in their professional life, the more effective a professional they become. We're developing a deep understanding of the professional world, mapping people, companies, and the information that flows between them through natural language processing and machine learning. Our team is a diverse, outspoken group of creatives and critical thinkers, hyper-focused on driving enterprise growth. We embrace different. We applaud non-traditional career paths. We're inspired by people who have made processes their own.
Position
As a Senior Software Engineer on Intelligence Platform Team you will help to develop and scale People.ai foundational technology — building an accurate map of the business world, based on people and their relationships. You will deliver new functionality such as identity resolution, tap into previously unused data sources, systematically increase data quality and extract new knowledge from people.ai data.
Responsibilities
- Work with the engineering team, product and customer success, designed and built new features in Intelligence Platform that substantially improve data richness and power multiple new use cases within people.ai platform
- Leverage knowledge of data analysis and information retrieval techniques to extract signal from existing data, thus driving up data quality in a measurable and consistent manner
- Scale the Intelligence Platform through building efficient distributed services and data pipelines. Ensure robust operation by building observability tooling and minimizing the number of production incidents
- Partner with Customer Success team, participate in incident investigations and escalations, understand underlying problems, propose and implement solutions
- Accelerate the team’s velocity by following best practices of software development, delivered clean, documented, and maintainable code. Ensure monitoring, ease of debugging and tracing. Build the necessary tooling to enable the customer support team to investigate and solve support requests in a self-service manner
Your qualification
- Working with data:
- Experience in analyzing large datasets and making data-driven decisions
- Know the basics of statistical analysis and ML
- Experience with Spark or other ETL / big data processing engines (Hive/Hadoop/MapReduce or Apache Storm, Apache Samza, etc.)
- Problem-solving:
- Passionate about problem-solving
- Demonstrate analytical thinking and problem-solving skills by successfully solving a technical problem and implementing it in code. Deliver an elegant, practical, and easy to follow solution
- Engineering excellence:
- Passionate about quality, reliability, and maintainability. Advocate for best practices and software patterns in the interest of producing clean, maintainable code
- Experience in taking ownership and working in an unfamiliar codebase of variable quality. Able to simplify and gradually improve existing code and systems
- Gravitate towards automation and reducing manual operations. Able to build reusable tooling for their own team, as well as downstream teams and customer support
- Distributed systems:
- Experience in building and maintaining distributed systems in the cloud (AWS)
- Demonstrate ability to design, build, monitor, and operate highly scalable data-intensive applications
- Working with business:
- Accustom to working with business teams directly to gather requirements and deliver solutions to business needs. Can leverage technology to solve business problems. Motivated by real-life business problems
- Able to strike a good balance between delivering to business needs and building maintainable software systems