Senior Software Engineer, Platform

Senior Software Engineer, Platform

Location

New York, NY

Work Arrangement: On-site, at least 4 days per week

Relocation: Open to relocation for the right candidate. New York-based candidates are strongly preferred.

Company Stage

Series A | Approximately 30 employees | AI / Enterprise Software / Data

Compensation

• Base Salary: $180,000–$200,000

• Equity: 0.1%, vesting over 4 years with a 1-year cliff

• Benefits: Medical, dental, vision, 401(k) with company match, HSA matching, and unlimited PTO

Visa

No visa sponsorship or visa transfers. Candidates must already be authorized to work in the United States without sponsorship, such as U.S. citizens or Green Card holders.

Company Description

We are an AI-native enterprise software company helping some of the world's most recognizable consumer brands better understand their customers and build better products.

Our platform acts as an AI-powered Voice of Customer analyst, aggregating and analyzing millions of consumer feedback records from product reviews, ratings, social conversations, customer support interactions, and other sources. Using generative AI, natural language processing, deep learning, and agentic workflows, the platform transforms unstructured feedback into structured insights that help businesses identify emerging trends, understand customer sentiment, uncover competitive intelligence, and make better product and marketing decisions.

The platform supports teams across consumer goods, consumer electronics, personal care, food and beverage, and other industries. Customers use these insights to refine product strategies, improve retail performance, and better understand consumer needs.

The company is building an AI-first engineering organization in New York, with a strong emphasis on ownership, autonomy, practical AI adoption, and shipping production-ready software.

What You Will Do

• Build scalable data infrastructure: Design and develop data models, integrations, and pipelines that power an AI-native Voice of Customer platform processing millions of consumer feedback records.

• Own platform capabilities end-to-end: Take responsibility for the complete lifecycle of platform features, including data modeling, pipelines, APIs, backend infrastructure, and observability.

• Build AI-powered and agentic workflows: Research, evaluate, and select appropriate models, then build production-ready workflows using LLMs, APIs, and Model Context Protocol (MCP).

• Translate customer needs into platform capabilities: Partner with product managers and product engineers to turn business requirements into traditional software features and AI-driven functionality.

• Develop internal data-management tools: Build interfaces and tools within the platform that help internal teams manage data and operate the product effectively.

• Improve engineering velocity: Identify and adopt AI-assisted development tools, new models, and engineering practices that improve development speed, code quality, and maintainability.

• Collaborate cross-functionally: Work closely with Product, Design, Sales, and Customer Success to understand customer requirements, support implementations, and troubleshoot technical issues.

• Operate with autonomy: Take ownership of complex engineering problems, make sound technical decisions, and deliver meaningful outcomes without constant direction.

Ideal Candidate Background

Required Experience

• 3+ years of professional software engineering experience building and shipping production software.

• An undergraduate degree from an accredited institution; a specific university or degree discipline is not required by the role brief.

• Experience designing and building scalable data models, data pipelines, and data integrations.

• Strong backend engineering fundamentals, including APIs, data architecture, and production infrastructure.

• Experience taking projects from initial design through implementation, deployment, and ongoing maintenance.

• Experience working independently in a high-ownership environment with minimal supervision.

• Ability to collaborate effectively with product and business stakeholders.

Technical Skills

• Python: Strong preference for candidates who use Python in their backend or data engineering work.

• Data modeling: Experience designing reliable, scalable data models for complex datasets.

• Data pipelines and integrations: Experience ingesting, transforming, processing, and connecting data from multiple sources.

• Backend engineering: Experience building APIs, backend services, and infrastructure that support product functionality.

• LLMs and generative AI: Familiarity with integrating large language models into real-world applications.

• Agentic workflows: Experience building or deploying workflows that use LLMs, APIs, tools, or multi-step reasoning to accomplish tasks.

• MCP: Familiarity with Model Context Protocol is relevant to the role.

• Observability: Understanding of monitoring, debugging, reliability, and maintaining production systems.

• NLP: Exposure to natural language processing or systems that analyze unstructured text is beneficial.

Preferred Background

• Experience at an AI-native product company or a startup building AI-powered enterprise software.

• Experience bringing LLM-powered or agentic applications into production rather than working exclusively on prototypes.

• Experience evaluating and selecting models beyond relying solely on the most commonly used providers, such as OpenAI or Anthropic.

• Experience processing large volumes of unstructured data, including reviews, social conversations, customer feedback, or support tickets.

• Experience with enterprise data platforms, customer intelligence, analytics, or data-heavy applications.

• Experience working on a small engineering team where individual contributors own entire capabilities.

• Familiarity with AI-assisted coding and modern developer tools.

Working Style and Culture

• High ownership: Takes responsibility for outcomes rather than waiting for detailed instructions.

• Strong execution: Has a track record of delivering projects and shipping production software.

• Autonomous: Comfortable making technical decisions and driving work forward without micromanagement.

• AI-forward: Actively explores new AI models and development tools and applies them pragmatically.

• Product-minded: Understands how technical decisions affect customers, product capabilities, and business outcomes.

• Collaborative: Comfortable working with engineers, product managers, designers, Sales, and Customer Success.

• Practical engineer: Focuses on solving real-world problems rather than prioritizing academic research over applied engineering.

• Long-term builder: Demonstrates reasonable career stability and the ability to build and improve systems over time.

Compensation and Benefits

• Base salary of $180,000–$200,000.

• 0.1% equity, vesting over four years with a one-year cliff.

• Medical, dental, and vision insurance.

• 401(k) with a 4% company match.

• HSA matching.

• Unlimited paid time off.

• Free lunches in the office.

• Support for professional development and career growth.

• Access to a modern AI-first technology stack and development tools.

• Opportunity to take ownership of core platform capabilities within a growing engineering organization.

Why Join?

• Build practical AI systems: Work on production AI applications that analyze millions of consumer feedback records and help global brands make better decisions.

• Own meaningful engineering work: Take responsibility for complete capabilities across data infrastructure, backend systems, APIs, and agentic workflows.

• Shape a growing platform team: Join a small engineering organization that is bringing its platform and product engineers together in New York.

• Work in an AI-first environment: Explore and adopt new models, agentic frameworks, and development tools instead of limiting engineering decisions to a fixed stack.

• Collaborate across the business: Work closely with Product, Design, Sales, and Customer Success to build solutions grounded in real customer needs.

• Operate with autonomy: Make decisions, solve complex problems, and see the impact of your work without layers of management.