4 hours ago
Responsibilities
- Embed with customers to understand their businesses and identify high-value AI opportunities.
- Turn ambiguous customer problems into product direction and technical plans.
- Choose architectures and make build-versus-buy decisions.
- Build and ship complete production systems rather than isolated components.
- Own a workstream, determine scope and sequencing, and serve as the client’s technical voice.
- Measure production outcomes, identify when scope is wrong, and continuously improve shipped systems.
- Develop reusable agent systems, evaluations, and tools for future engagements.
- Work on agent orchestration, evaluation, memory, and long-running execution at the frontier of reliable production AI.
Requirements
- Have shipped production software that real users depended on.
- Have built a real system with LLMs and can explain its strengths and limitations.
- Become productive in unfamiliar business and technical domains within days.
- Explain technical decisions clearly to both CEOs and engineers.
- Use AI daily in personal engineering work and have informed opinions about effective usage.
Benefits
- Work together in Manhattan five days a week.
- Base salary, quarterly bonus, and equity are offered, with specific compensation details shared in the offer.
- Fast hiring process with six interview steps and quick decisions.
Categories
AI ApplicationsForward Deployed
About Tenex
This AI thing, it’s real. As real as mobile, the internet, and each of the major paradigm shifts in technology that came before it. In fact, we think it’s more real. More powerful. More disruptive to how we work & how businesses operate. This leaves you with a choice. Disrupt yourself. Or be disrupted by others. Because as the cost of intelligence approaches zero, businesses will need to transition from AI-absent to AI-native if they want to stay relevant and succeed.