Offer summary

Qualifications:

3+ years of professional experience in developing distributed systems in a cloud environment, preferably AWS., Strong experience in analyzing large structured and unstructured datasets., Proficiency with Spark or equivalent big data processing engines., Bachelor’s Degree in Computer Science, Computer Engineering, or a closely related discipline..

Key responsabilities:

Enhance and maintain scalable LLM inference pipelines for actionable deal assessments.

Develop and implement new AI features, integrating external data sources into deal risk assessments.

Improve monitoring systems to enhance pipeline visibility and reduce failure resolution time.

Write clean, maintainable code and build tooling for customer support teams.

Job description

People.ai is an AI-powered foundational data platform that helps customers unlock go-to-market success & growth by providing teams with solutions built specifically for their needs. Providing enhanced pipeline visibility, more actionable insights, and a single source of truth for all sales activities. People.ai’s unique dataset, consisting of trillions of sales activities, millions of deals, 160 million business contacts, and 69 approved patents related to AI-based business insights, sets the company apart. They have a comprehensive list of top Fortune 500 companies that rely on their enterprise-ready, patented AI technology.

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. Our team is a diverse, outspoken group of creatives and critical thinkers, hyper-focused on driving change and growth. We embrace different. We applaud non-traditional career paths. We're inspired by people who have made processes their own.

As a Software Engineer on the Revenue Stories team, you will enhance and maintain scalable LLM inference pipelines that transform communications into actionable deal assessments and insights. You will build new AI-driven capabilities, improve monitoring and debugging efficiency, and optimize pipeline scalability. Collaboration with cross-functional teams to align solutions with business needs is essential.

Responsibilities:

Improve and optimize critical LLM inference pipelines to generate high-quality deal assessments while maintaining cost efficiency.

Develop and implement new AI features, such as integrating external data sources (e.g., company news) into deal risk assessments.

Enhance monitoring systems to improve pipeline visibility, accelerate debugging, and reduce failure resolution time by 50%.

Scale inference pipelines effectively to handle increased volumes, targeting 5 million AI-generated insights monthly.

Write clean, maintainable, and well-documented code, following engineering best practices.

Build tooling to enable customer support teams to independently resolve common issues.

Demonstrate behaviors consistent with our Engineering Leveling Guidelines.

Requirements:

3+ years professional experience developing distributed systems in a cloud environment (AWS preferred).

Strong experience analyzing large structured and unstructured datasets.

Proficiency with Spark or equivalent big data processing engines (Hive, Hadoop, MapReduce, Storm, Samza).Experience using Large Language Models (LLMs), familiarity with prompting techniques (chain-of-thought, RAG), and knowledge of common market models.

Understanding of LLM limitations and strategies to mitigate them.

Proven problem-solving abilities, with practical and elegant coding solutions.

Passionate about engineering excellence—advocates for high-quality, reliable, and maintainable software.

Experience improving existing codebases, automation, and tooling for operational efficiency.

Bachelor’s Degree in Computer Science, Computer Engineering, or closely related discipline.

Nice to Have:

Familiarity with Elasticsearch and Kafka.

Experience with fine-tuning or advanced inference techniques for LLMs.

Headquartered in San Francisco, CA, People.ai is backed by Y Combinator and Silicon Valley’s top investors, including ICONIQ Capital, Andreessen Horowitz, Lightspeed Venture Partners, Akkadian Ventures, and Mubadala Capital. People.ai is listed in the top 20 percent of Inc 5000 companies, is a regular leader in our key categories on G2, and is on the Forbes list of America’s Best Startup Employers. For more information, please visit www.people.ai.

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