Artificial Intelligence (AI), Benchmarking, Business Solutions, Business-to-Business (B2B), Compensation and Benefits, Computer Science, Construction, Customer Relationship Management (CRM), Deep Learning, Environmental Research, Experiment Design, Leadership, Mathematics, Natural Language Processing (NLP), Product Development, Production Systems, Publications, Reinforcement Learning, Sales, Software Engineering, Software as a Service (SaaS), Startup, Statistics, Storage Area Network (SAN), Structured Data, Systems Engineering, Technical Leadership, Technical Strategy, Unstructured Data
We're working with an early-stage, well-funded AI startup in San Francisco, building an AI-powered revenue intelligence platform designed to help modern revenue teams make faster, better decisions.
The platform acts as “AI headcount” for GTM teams, helping Sales, RevOps, and Leadership teams understand what's happening in their business and why by connecting CRM data, customer calls, emails, internal knowledge, and other business systems through a conversational AI interface.
The company recently launched publicly and is already working with well-known B2B SaaS organizations. They're backed by top-tier investors including Insight Partners, GV (Google Ventures), Sequoia Capital, and Lightspeed.
About the Role
They're hiring an Applied AI Research Engineer to help build the core intelligence systems behind our AI revenue agent.
This role sits at the intersection of applied research, agent systems, and production engineering. You'll work on the core behavior and reasoning systems that power the platform, including tool use, context construction, multi-agent coordination, evaluation systems, scoring models, and long-horizon reasoning workflows.
You'll own ambiguous technical problems end-to-end: designing experiments, improving model behavior, building evaluation frameworks, and shipping systems into production.
This is a highly technical, hands-on role working closely with the founders and engineering team in a fast-moving environment where research quickly becomes product.
What You'll Do
- Build and improve the core agent systems powering the platform
- Develop tool-use strategies, context management systems, and multi-step reasoning workflows
- Design and implement evaluation pipelines, regression detection systems, and benchmarking frameworks
- Research and improve model behavior across complex revenue and business tasks
- Build scoring and prediction systems using structured and unstructured data
- Improve context engineering, retrieval systems, entity resolution, and knowledge graph quality
- Experiment with reinforcement learning and agent optimization approaches
- Work across the full lifecycle from experimentation to production deployment
- Partner closely with founders and engineering leadership on product direction and technical strategy
What We're Looking For
- Strong experience working with LLMs, deep learning systems, or modern AI infrastructure
- Experience building or evaluating agentic systems, including tool use, reasoning workflows, or multi-agent coordination
- Strong software engineering fundamentals and ability to ship production-quality systems
- Ability to independently scope ambiguous technical problems and drive toward solutions
- Experience designing experiments, evaluation frameworks, or benchmarking systems
- Strong understanding of model behavior, prompting, fine-tuning, or RLHF concepts
- Comfortable operating in fast-moving startup environments with high ownership
Nice to Have
- Experience with retrieval systems, vector databases, or knowledge graphs
- Experience building AI products in production environments
- Background in reinforcement learning or optimization systems
- Publications or research experience in ML, NLP, or related fields
- MS or PhD in Computer Science, Mathematics, Statistics, or related quantitative discipline
Why Join
- Early technical hire with meaningful ownership and influence
- Opportunity to work on frontier agent systems and applied AI problems
- Direct collaboration with founders and technical leadership
- Fast-moving, highly technical environment with real product impact
- Competitive compensation, equity, and benefits
- In-office team environment in San Francisco
Compensation & Benefits
- Base: $150,000–$250,000
- Equity is included as part of the compensation package
Additional benefits include:
- Comprehensive medical, dental, and vision coverage
- 401(k)
- Unlimited PTO
- Daily in-office lunch and fully stocked kitchen
Compensation Transparency
- The compensation range for this position is reflective of full-time employment and will vary based on factors unique to each candidate, including skill set, experience, and location.
- Roles are leveled based on competencies. If an offer is extended, the final title and compensation may be adjusted to align with your experience and interview performance.
- We evaluate candidates based on merit and qualifications. We are committed to building an inclusive environment and welcome applicants of all backgrounds.