Expertise in both conventional and modern ML methodologies
Proven track record of driving end-to-end project ownership
Experience implementing agent-driven development practices
Background in data-intensive B2B product environments
Ability to navigate ambiguous situations and tasks
Excellent communication skills for direct enterprise engagement
Responsibilities
Lead design and delivery of revenue agents, initially as an individual contributor
Set engineering standards and practices for the team
Own the architecture of the core agent platform and make infrastructure decisions
Collaborate with the CTO to guide technical direction and product roadmap
Manage performance and growth of the engineering team
Hire new team members and lead difficult conversations
Oversee the integration of customer data into a unified representation
Benefits
Opportunity for deep involvement in both engineering and management
Work closely with executive leadership in shaping strategic direction
Involvement in cutting-edge machine learning initiatives
Strong emphasis on individual contributions early in the role
Focus on a collaborative and growing team environment
Access to diverse challenges in a dynamic B2B context
Full Job Description
What you'll do
Lead the design and delivery of production-grade revenue agents. We believe the best engineering leaders stay close to the work. You operate as an IC for your first 3-6 months, then evolve into managing and growing the team while continuing to ship yourself.
Set the engineering bar for a team where agents write most of the code. Review standards, definition of done, release cadence, on-call, incident response, sprint scope and sequencing. You inherit two strong engineers and hire everyone who comes after, which includes performance management and the conversations nobody wants to have.
Own the architecture behind our core agent platform. The ontology and semantic layer that reconciles every customer's warehouse into one representation, the signal pipeline that sits on top of it, and the transformer work ahead of us. You make the build-versus-buy calls and the infra cost decisions.
Share technical direction with our CTO and shape the platform. Product roadmap and sequencing, ML approach, model strategy, hiring loop design, closing candidates. Your team's work across deployments decides which patterns generalize into the world model and which are artifacts of a single warehouse. Shangyan holds final say on ML direction and product, and we are hiring someone who will disagree with him and be right often enough to matter.
What you'll bring
4+ years of industry experience in software engineering
Deep, current ML across both eras: feature engineering, uplift and causal methods, time series, and calibration alongside transformers, world models, and agent architectures
End-to-end delivery ownership somewhere nobody above you was catching failures, where you built the scaffolding rather than inheriting it working
Fluency in agent-driven development as a practice, having changed how your team reviews, tests, and specs work because of it
Data-intensive B2B product background: warehouse-native, per-tenant, enterprise data access
High tolerance for ambiguity and unglamorous work
Strong communication skills and ability to work directly with enterprise customers
