Engineering Lead

Location

San Francisco, CA or New York, NY

Hybrid — 2 days per week in-office on Tuesdays and Thursdays.

Company Stage of Funding

Growth Stage / VC-Backed

Office Type

Hybrid — 2 days per week in-office

Salary

$221,000 – $295,000 Base

Equity

Competitive Equity

Visa

Open to Visa Transfers, including OPT and H-1B transfers. Additional sponsorship may be considered on a case-by-case basis.

Experience

6+ years of software engineering experience, with at least 2 years of formal engineering management experience.

Employment Type

Full-time

Hiring Count

1 candidate

Company Description

This is a growth-stage technology company building an AI-powered platform that changes how people work with data.

The company is evolving from a traditional analytics platform into an increasingly agentic AI platform, enabling users to work with data through intelligent, collaborative, and shareable workflows. Its products are used by tens of thousands of people for sophisticated analytical work.

The engineering organization is structured around several core pillars, including analytics, context, and platform. This role will lead the context engineering pillar, which sits at the center of the company's broader AI strategy.

The context platform helps users understand how AI agents interact with their data, identify where AI quality falls short, and improve the context that drives better outcomes. The team is building a new development lifecycle for AI context that combines human insight with automated learning and iteration.

This is a hands-on engineering leadership role. The ideal candidate is an engineering manager who can set technical strategy, manage and develop engineers, recruit exceptional talent, and continue contributing directly to technical decisions and production systems.

What You Will Do

1. Lead & Develop a High-Caliber Engineering Team

• Lead a team of engineers building the company's AI context platform.
• Manage approximately 3–15 individual contributor engineers as the organization grows.
• Set clear expectations and empower engineers to take meaningful ownership.
• Coach engineers toward stronger technical and product judgment.
• Build a culture of high standards, collaboration, and accountability.
• Recruit and hire exceptional engineering talent as the team scales.
• Support the growth and development of engineers across different levels of seniority.
• Maintain a strong technical presence while operating as a people manager.

2. Drive Technical Strategy & Stay Hands-On

• Own and influence the technical strategy for the context engineering pillar.
• Review system designs and architectural proposals.
• Continue contributing directly to engineering work and technical decisions.
• Help the team solve complex problems around AI context, agent reasoning, and data systems.
• Evaluate technical tradeoffs and guide the team toward scalable, maintainable solutions.
• Establish strong engineering standards around architecture, code quality, testing, and execution.
• Partner with senior technical leaders to shape the broader engineering architecture.

3. Build & Scale AI-Native Products

• Lead development of an AI-native context platform used by thousands of analytical users.
• Build systems that help users understand, improve, and manage the context available to AI agents.
• Work on problems involving agent reasoning, context management, AI quality, and human-in-the-loop workflows.
• Help build systems that detect, debug, and improve failures in AI agent behavior.
• Partner with product and engineering teams to turn complex AI problems into reliable customer-facing products.
• Help evolve the platform from traditional analytics workflows toward increasingly agentic experiences.
• Connect engineering decisions to measurable product and customer outcomes.

4. Scale the Engineering Organization & Cross-Functional Strategy

• Help define the technical roadmap for the context engineering pillar.
• Partner closely with product, design, and other engineering leaders.
• Work cross-functionally to align technical strategy with company and product goals.
• Build processes that allow the engineering organization to scale effectively.
• Help the team operate with high agency while maintaining strong engineering quality.
• Work closely with senior leadership on organizational priorities and technical direction.
• Contribute to hiring strategy, team structure, onboarding, and long-term engineering growth.

Ideal Candidate Background

Experience Requirements

• 6+ years of professional software engineering experience.
• At least 2 years of formal engineering management experience.
• Experience as an Engineering Manager, Engineering Lead, Tech Lead Manager, or equivalent.
• Experience managing approximately 3–15 individual contributor engineers.
• Experience leading engineers through significant product or organizational growth.
• Experience working in a high-growth startup environment, ideally within the last three years.
• Strong track record of owning meaningful technical and organizational outcomes.
• Experience building external, customer-facing products.
• Strong product instincts and strategic thinking.

Technical Requirements

• Strong full-stack software engineering background with a clear product-engineering orientation.
• Strong proficiency in TypeScript.
• Experience with React is preferred.
• Experience with Postgres is preferred.
• Strong system design and architecture skills.
• Experience reviewing technical designs and making architectural decisions.
• Current or recent hands-on engineering contribution.
• Strong understanding of modern software engineering practices and production systems.
• Comfortable working across the product stack rather than being narrowly specialized in infrastructure, mobile, or analytics.

AI & Product Requirements

• Hands-on experience building or working on an agentic or AI-native product within the last 2–3 years is required.
• Experience building production AI-powered products rather than simply using AI development tools.
• Strong understanding of AI-native product development and user-facing AI workflows.
• Experience with agentic systems, AI context, retrieval, or AI-powered workflows is highly valued.
• Experience with Python is a plus.
• Strong product instincts and ability to translate emerging AI capabilities into useful customer-facing products.
• Ability to connect technical decisions to customer adoption and product outcomes.

Leadership & Soft Skills

• Strong people leadership and coaching skills.
• Able to set a high engineering bar while empowering engineers to operate independently.
• Strong product and strategic judgment.
• Comfortable managing and developing engineers across different levels.
• Strong hiring and team-building instincts.
• Excellent cross-functional communication.
• Comfortable working closely with product, design, and senior engineering leadership.
• High ownership and accountability.
• Comfortable operating in a fast-moving startup environment.
• Able to balance technical depth, people leadership, and product execution.

Compensation & Benefits

• $221,000 – $295,000 base salary.
• Competitive equity package.
• Full-time position.
• Hybrid work model with 2 days per week in-office.
• Office locations in San Francisco or New York City.
• Opportunity to lead a core engineering pillar focused on AI context and agentic systems.
• Significant technical and organizational ownership.
• Opportunity to work on an evolving AI-native platform with a large active user base.

Why Join

• Lead a core engineering team building the next generation of AI-powered data products.
• Work directly on agentic systems and AI context infrastructure.
• Help define how users understand, manage, and improve AI behavior with their data.
• Combine engineering leadership with meaningful technical contribution.
• Work in a collaborative, high-agency engineering organization.
• Shape technical strategy for a critical engineering pillar.
• Build and scale a team of talented product engineers.
• Work at the intersection of AI, data, analytics, and product engineering.