Lead engineering at a pre-seed GenAI startup: define architecture and tech stack, build the first B2B enterprise SaaS product, set up cloud infrastructure, DevOps and CI/CD, ensure code quality, hire and manage 1-2 engineers, and apply LLM/ML expertise to drive product and business strategy.
Overview
Why GuideSage
Key Responsibilities
Ideal Profile
GuideSage, PBC is a venture-funded, pre-seed, stealth, agentic AI startup with a mission to responsibly help people reach their full potential through learning. We have a multi-product strategy to improve the way people learn using thoughtfully applied generative AI and ML. This year, we’re focused on building our first product, which will target the $400B corporate training market and define a new category.
GuideSage was founded by Adam Berrey, who brings 28 years of experience building successful software companies, including several IPOs and exits. We're actively building our product development team and looking for a founding software engineer to lead development and help build the company. Our vision is to create a generational company that uses agentic AI to help everyone learn more.
This is an opportunity to come in at the ground floor and shape every aspect of the product and business with the confidence that the company already has a clear business strategy and strong funding.
- Mission-driven commitment to positively contribute to the world by helping people learn
- Full competitive salary, benefits, and meaningful equity on day one
- Freedom to craft great software and create a brand-new product from scratch
- Flexibility to build a team you love working with
- Clear business model, product strategy, and prospective customers
- Opportunity to work at the cutting edge of applying GenAI and ML to solve real-world business problems in a $400 billion market with an even larger impact on how people learn everywhere
- Collaborate with co-founders, business stakeholders, and designers to iteratively create the product vision, strategy, and roadmap
- Develop the software and lead the engineering work to create a product that users love and customers buy
- Establish the technical foundation, including the architecture, infrastructure, and tech stack
- Decide on the programming languages, frameworks, and tools based on the company’s needs, scalability, and product goals
- Setup the necessary infrastructure to build and deploy the software, including cloud services, DevOps, CI/CD, and other tools and services
- Ensure code quality, setting up best practices for the development process, and fostering a strong engineering culture
- Hire and manage 1-2 engineers and shape the engineering team's culture, including communication norms, pace, and stage-appropriate work processes
- Stay current with the latest developments in AI and bring insights to the business and product strategy
- Help to define and shape the culture of the company
- Exceptional software engineering and coding skills
- Proven ability to work in a fast-changing, high-uncertainty startup environment
- Great at making technology stack, build/buy, and architecture choices
- Experience building commercial B2B enterprise SaaS systems
- Experience working in early-stage startups or teams building from zero to one
- Experience building on LLM APIs and working with ML
- Capable of building and leading a small engineering team
- Interested in the mission
Similar Jobs
Artificial Intelligence • Machine Learning • Marketing Tech • Natural Language Processing • Sales • Software
Own product features end-to-end across web app, GraphQL API, and embeddable components. Design schemas and APIs, build backend and frontend, write tests, monitor real-user behavior, and ship weekly. Establish shared component library, design system, and testing patterns. Optimize performance and leverage AI tooling to accelerate engineering and product collaboration.
Top Skills:
FastapiFigmaGraphQLPostgresPythonReactStorybookStrawberry GraphqlTailwindTypescript
Artificial Intelligence • Consumer Web • eCommerce • Gaming • Mobile • Software • Analytics
Own the development of a 24/7 agent that monitors retailer drops, detects scarce inventory, automates checkout, tracks portfolios, and supports real-time pricing infrastructure. The role offers high autonomy, broad technical ownership, and responsibility for reliable production systems serving thousands of collectors. This is a full-time, in-person position in New York City.
Artificial Intelligence • Fintech • Machine Learning • Financial Services
Build the core infrastructure for an AI-native investment research and automated trading platform. Responsibilities include experiment environments, compute orchestration, storage, observability, deployment pipelines, sandboxed agent tooling, data ingestion and versioning, backtesting, production reliability, monitoring, failure recovery, and AI-native engineering practices. Collaborate closely with researchers and quants to move ideas from experiments into deployed strategies.
Top Skills:
Agentic SystemsAIBacktestingCiCloud StorageCompute OrchestrationData IngestionData PlatformsData VersioningDeployment PipelinesDistributed SystemsLow-Latency ServicesMachine LearningMl InfrastructureObservabilitySandboxed Code ExecutionSoftware Evaluation Harnesses
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
