Principal AI Software Engineer, GTM
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal AI Software Engineer, GTM based in United States.
This is a high-impact engineering role focused on applying AI to transform go-to-market operations.
You will build intelligent products and services that help internal teams make better decisions and operate more efficiently.
The role combines software engineering, product thinking, data, automation, and AI agent development.
You will own problems end-to-end, from discovery and rapid prototyping through production launch, measurement, and iteration.
You will also create reusable AI infrastructure and patterns that enable other engineers to build safely and consistently.
Success requires an entrepreneurial mindset, strong technical judgment, and a willingness to turn ambiguous problems into working solutions.
You’ll operate in a distributed, customer-focused environment where AI-native engineering, speed, reliability, privacy, and measurable business impact are highly valued.
Accountabilities:
- Own meaningful technical and operational problems from discovery through design, implementation, launch, measurement, and continuous improvement.
- Design and build AI-powered products and cross-cutting services that improve go-to-market workflows, decision-making, productivity, and operational effectiveness.
- Develop AI capabilities such as retrieval, contextual intelligence, evaluation frameworks, tool use, orchestration, guardrails, and agent workflows.
- Work as a hybrid product, engineering, and data builder by engaging internal users, defining success metrics, shaping workflows and user experiences, developing evaluation plans, and iterating rapidly from prototype to reliable production systems.
- Prototype quickly and use working software, AI agents, coding tools, scripts, and automation to validate assumptions and create clarity around complex problems.
- Create shared AI abstractions, tooling, monitoring, logging, prompt patterns, and reusable components that establish a consistent foundation for engineering teams.
- Shape data and system architecture so AI can safely connect longitudinal signals across product, billing, support, operations, and go-to-market systems to recommend and execute appropriate next actions.
- Raise standards for engineering quality, reliability, observability, security, privacy, and customer trust across AI-powered solutions.
- Use AI extensively within your own development workflow to increase speed and effectiveness while maintaining a high quality bar.
- Mentor and influence other engineers by demonstrating AI-augmented engineering practices and helping raise the organization’s capabilities in AI development.
- Collaborate closely with internal customers and cross-functional stakeholders to develop creative solutions that address business objectives rather than simply implementing predefined requirements.
- 8+ years of professional software engineering experience with strong fundamentals across systems, data, APIs, product surfaces, and infrastructure.
- Demonstrated ownership of production software from problem definition and discovery through launch, measurement, and iteration.
- Proven experience using AI tools and agents as an integral part of an engineering workflow, with examples of improving personal, team, or organizational productivity through automation.
- Strong ability to operate independently in ambiguous environments, identify high-value problems, establish direction, and turn unclear requirements into shipped software.
- Experience building production-quality software with strong attention to reliability, security, privacy, observability, scalability, and customer trust.
- Strong communication and collaboration skills, with the ability to work effectively with internal customers and cross-functional teams.
- Experience designing or building AI-powered products, workflows, internal tools, or systems is highly valuable.
- Experience with retrieval, tool use, evaluation, monitoring, orchestration, agent workflows, or related AI engineering patterns is preferred.
- Experience in operations-heavy environments such as vertical SaaS, education, fintech, healthcare, CRM, ecommerce, or similar domains is a plus.
- A demonstrated builder mindset through personal projects, internal tools, open-source contributions, technical writing, demos, or other work showcasing experimentation and initiative is valued.
- Familiarity with modern AI and cloud technologies such as AWS Bedrock, Bedrock AgentCore, hosted LLMs, LangChain, LangGraph, vector and semantic search, and AI coding tools such as Cursor, Claude Code, or Codex.
- Experience with Python, FastAPI, asynchronous workers, queue-based architectures, PostgreSQL, Redis, DynamoDB, Redshift, data pipelines, React/TypeScript, AWS infrastructure, Docker, Kubernetes, CI/CD, and cloud services is beneficial.
- Competitive compensation package aligned with experience, skills, and role scope.
- Remote work environment with distributed teams across U.S. time zones.
- Opportunity to work on production AI systems with direct, measurable impact on business operations.
- Access to modern AI development tools, cloud infrastructure, agent orchestration technologies, and data platforms.
- Collaborative environment emphasizing customer focus, ownership, accountability, innovation, and high-quality execution.
- Opportunity to influence AI engineering standards, reusable infrastructure, and emerging product capabilities.
- Strong emphasis on professional growth, technical leadership, experimentation, and mentorship.
- Inclusive and equal-opportunity workplace committed to supporting diverse backgrounds and perspectives.
- A role with significant autonomy and the opportunity to shape solutions rather than simply execute predefined requirements.