Principal AI Software Engineer, GTM

1 нед. назад

194k–263k USD / yearUSALeadRemote

Develop AI-driven features for a vertical SaaS platform in early education to automate and enhance workflows for school leaders, teachers, and families.

О компании

Early education is one of the most important determinants of childhood outcomes, a critical support for working families, and a $175B market that remains underserved by modern technology. is the largest, fastest growing, and most loved platform in early ed, trusted by millions of educators and families every day. We are a three-time Cloud 100 company , backed by top investors including Addition, Bessemer, Emerson Collective, Lowercase Capital, Notable Capital, and Mark Cuban.
Our team is passionate, talented, and customer-focused. We embody our Leadership Principles in our work and culture. We are a distributed team with remote employees across every US time zone, as well as select offices in the US and internationally.

Обязанности

Our team is passionate, talented, and deeply customer-focused. We build the platform that thousands of early education programs rely on every day to run their business, serve families, and support children’s growth. As a vertical SaaS company, already sits in the middle of all the key workflows in early education: enrollment, billing, staffing, classroom planning, and family communication. We are now extending that foundation into a system of action – where software not only records what happened, but also anticipates work, recommends next steps, and takes safe, automated action on behalf of school leaders, teachers, families, and our internal teams.
We’re looking for an AI-native software engineer to join our GTM engineering team. This role is for someone who wants to make a direct impact upon the bottom line. You will design and build AI solutions to solve the challenges internal teams wrestle with on a daily basis. You will build products that allow our go-to-market team to operate at peak performance–delivering the right information at the right time. You will build solutions that allow AI agents to take action on operational data, accelerating the operations of internal teams. You will lead by example in AI-augmented engineering, using AI to multiply your own speed, mentoring other engineers, and raising the bar for how we design, ship, and operate AI-powered features.
The best candidates do not wait for perfect requirements. They prototype quickly, validate assumptions with users or internal teams, define success metrics, and iterate in production. They use AI agents, coding tools, scripts, and automation to move faster, while raising the bar for quality, reliability, privacy, security, and customer trust.

Другое

Own meaningful problems from discovery through launch, measurement, and iteration.
Use AI to improve both how you build and what can deliver.
Prototype quickly, validate assumptions, and use working software to create clarity.
Raise the bar for quality, reliability, security, privacy, observability, and execution.
Design and build cross-cutting AI services (such as retrieval, context, evaluation, and guardrails) that power go-to-market operational workflows, optimizing the efficacy of internal teams.
As a hybrid PM+Eng+Data builder: own the end-to-end product loop for the problems you take on: talk to customers and internal teams, define the success metric, design the workflow and user experience, shape the data and evaluation plan, and ship iterative releases from prototype to reliable, scalable production.
Create shared abstractions and tooling for AI – for example, common prompt and tool patterns, logging and monitoring, and reusable components – so other engineers can build on a consistent foundation.
Shape our data and system architecture so AI can safely stitch together longitudinal signals across product, billing, support, and operations and recommend what should happen next, not just report what happened.
Have 8+ years of professional software engineering experience.
Have strong engineering fundamentals and can reason across systems, data, APIs, product surfaces, and infrastructure.
Have owned production work from problem definition through launch and iteration.
Use AI tools and agents as a real part of your engineering workflow, not as a novelty.
Can explain how you have increased your own velocity without lowering your quality bar.
Have examples of automating your own work, your team’s work, or broader company workflows.
Are comfortable operating in ambiguity and turning unclear problems into shipped software.
Communicate clearly and work well across functions.
Care deeply about privacy, security, reliability, and customer trust.
Strong candidates may also have
Experience shipping AI-powered products, workflows, or internal tools to production.
Experience with retrieval, tool use, evaluation, monitoring, orchestration, or agent workflows.
Experience in vertical SaaS, education, fintech, healthcare, CRM, ecommerce, or another operations-heavy domain.
A portfolio of personal projects, internal tools, open-source work, writing, demos, or side projects that shows builder energy and taste.
Experience building AI powered systems
Experience collaborating with internal customers; not only building out what is asked, but building out novel solutions that amplify those customers’ capabilities (thinking creatively to meet business objectives)
AI and Automation: AWS Bedrock and Bedrock AgentCore, other hosted large language models, LangChain and LangGraph agent orchestration, vector and semantic search, LangFuse, and modern AI coding tools like Cursor, Claude Code, and Codex
Backend: Python with FastAPI, async workers and queue-driven jobs
Data: PostgreSQL on Amazon RDS, Amazon Redshift, Redis, DynamoDB, and large-scale entity resolution, enrichment, and ingestion pipelines
Frontend: React with TypeScript, TanStack Query, Vitest and Cypress
Data Engineering and Integrations: Airflow, headless Chrome, S3-backed data lakes, and deep Salesforce integration alongside other GTM systems
Cloud and Infrastructure: Docker, Kubernetes on Amazon EKS, ECS Fargate, AWS CDK and CloudFormation, GitHub Actions and FluxCD for CI/CD, and AWS services such as S3, CloudFront, Lambda, SQS, and CloudWatch
is committed to creating a diverse and inclusive work environment and is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
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