Full-Stack Software Engineer

• Build and ship full-stack product features from concept through production using Go, Python, React, and TypeScript.
• Design scalable backend services, APIs, and data models that power AI-driven enterprise workflows.
• Develop intuitive frontend applications that transform complex datasets into actionable user experiences.
• Collaborate with machine learning engineers to integrate LLM-powered features and agentic AI capabilities into production.
• Own features throughout the entire development lifecycle, including architecture, implementation, testing, deployment, and iteration.
• Work directly with enterprise customers to understand product needs and rapidly translate feedback into software improvements.
• Contribute to cloud infrastructure, internal tooling, and developer experience as the engineering organization scales.
• Partner closely with product and design teams to deliver polished, customer-focused experiences.
• Help shape engineering standards, architecture, and technical direction within a rapidly growing startup.
• Thrive in a highly collaborative environment where engineers own both technical decisions and product outcomes.

Software Engineering, Startup, Artificial Intelligence (AI), Seed Funding, Product Strategy, Data Sets, Global Branding, Customer/Client Research, Forecasting, Marketing Strategy, * 3+ years of professional full-stack software engineering experience.

• Strong experience building production applications across both frontend and backend systems.
• Proficiency with React and TypeScript.
• Strong backend experience using Go or Python.
• Experience designing APIs, backend services, and scalable cloud applications.
• Familiarity with AWS and modern cloud deployment practices.
• Experience working within high-ownership startup environments.
• Bachelor’s degree in Computer Science or a related technical field.
• Strong product mindset with the ability to balance engineering quality and customer impact.

Preferred

• Experience building AI-powered applications, LLM integrations, RAG systems, or agentic AI workflows.
• Background in enterprise SaaS, data platforms, analytics, or retail technology.
• Experience with data engineering, data pipelines, or large-scale data processing.
• Familiarity with modern developer tooling, CI/CD pipelines, and infrastructure automation.
• Startup experience building products from zero to one.
• Strong communication skills with the ability to collaborate directly with enterprise customers.
• Comfortable working across the entire technology stack rather than specializing in a single area.
• Ability to thrive in fast-moving, ambiguous startup environments with significant ownership.

• Base salary: $120,000-$160,000.
• Competitive equity package.
• Five-day onsite collaboration in SoHo, New York City.
• Opportunity to join a well-funded seed-stage AI startup with established Fortune 500 customers.
• Significant ownership over product architecture and customer-facing features.
• Work directly with founders and a small, highly collaborative engineering team.
• Opportunity to help shape the future of AI-powered enterprise intelligence products.
• High-growth environment with meaningful opportunities for technical leadership and career development.

We’re representing a fast-growing AI startup building an enterprise intelligence platform that helps global brands transform fragmented consumer data into actionable business insights. Their AI-native platform unifies internal research, syndicated datasets, social signals, and other data sources into a single source of truth, enabling organizations to make faster, more informed decisions across marketing, product strategy, forecasting, and innovation.

Having recently closed a $14 million seed round and secured Fortune 500 customers including Gap, LG, and Xfinity, the company is expanding its engineering team as it launches its next phase of growth. You’ll join a small, high-caliber team building AI-powered enterprise software from the ground up while working directly with customers to shape the product.