> Markdown version of [/jobs/ext/4650388-senior-software-engineer-platform](https://www.wearedevelopers.com/jobs/ext/4650388-senior-software-engineer-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, Platform - **Company:** Recruiting from Scratch - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $180,000 - $200,000 - **Contract:** Permanent contract - **Skills:** Adaptable Database Systems, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Big Data, Software Quality, Data Architecture, Information Engineering, Data Infrastructure, Data Integration, Software Debugging, Programming Tools, Python (Programming Language), Machine Learning, Natural Language Processing, OpenAI, Software Engineering, Systems Integration, Unstructured Data, Enterprise Data Management, Enterprise Software Applications, Large Language Models, Deep Learning, Backend, Agentic-AI, Data Management, Api Design, Model Context Protocol, Data Pipelines - **Published:** November 9, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-platform-ny--14e65371-28c7-49f8-8f3f-795bc714f503 ## About the Role Software Engineering, Software Engineering, Enterprise Applications, Artificial Intelligence (AI), Consumer Branding, High Tech Industry, Product Development, Analysis Skills, Deep Learning, Competitive Analysis/Strategy, 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., * 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., * 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. ## Description * 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., * 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.