Principal AI Engineer
$206,600 - $284,300 per year
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Posted 12 days ago
SENIORITY
Manager
SALARY
$206,600 - $284,300 per year
About the role
- Define and drive the long-term technical strategy, reference architecture, and technology roadmap for AI-enabled products and platforms.
- Establish architectural patterns and best practices for retrieval systems, LLM orchestration, agentic workflows, human-in-the-loop processes, evaluation frameworks, and AI governance.
- Lead organization-wide technical decision-making regarding model strategy, vendor selection, platform investments, build-versus-buy decisions, and shared infrastructure capabilities.
- Design and champion scalable architectures that balance reliability, performance, security, compliance, maintainability, and cost efficiency.
- Establish engineering standards for evaluation, observability, model lifecycle management, responsible AI practices, and operational excellence.
- Build prototypes, proofs of concept, and reference implementations that de-risk emerging technologies and strategic platform investments.
- Lead cross-functional architecture reviews and provide technical guidance across multiple engineering teams.
- Mentor Lead Engineers, Senior Engineers, and emerging technical leaders through architecture reviews, design feedback, coaching, and technical sponsorship.
- Develop and communicate technical roadmaps aligned with business strategy and organizational objectives.
- Partner with executive leadership to translate business priorities into technical strategies and communicate technical opportunities, risks, and tradeoffs.
- Represent engineering in strategic vendor evaluations, compliance discussions, governance reviews, and enterprise planning initiatives.
- Drive adoption of common platforms, standards, and engineering practices across teams.
- Ensure AI systems are designed and operated in accordance with privacy, security, compliance, governance, and auditability requirements.
- Use your skills to make an impact Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.12+ years of software engineering experience, including extensive experience designing and operating large-scale distributed systems.
- Proven track record of designing, delivering, and operating production AI-enabled platforms or products at enterprise scale.
- Deep expertise in large language model technologies, AI platform design, retrieval-augmented generation (RAG), agentic systems, orchestration frameworks, evaluation methodologies, and AI operations.
- Extensive experience designing cloud-native architectures and highly scalable, resilient systems.
- Demonstrated ability to define technical direction that influenced teams, organizations, or product portfolios beyond direct reporting relationships.
- Experience establishing engineering standards, architectural frameworks, or technical platforms that have been successfully adopted across multiple teams.
- Strong understanding of AI operational challenges, including model reliability, latency, cost optimization, governance, observability, and risk management.
- Demonstrated success influencing executive stakeholders and driving organizational decisions through technical leadership and evidence-based recommendations.
- Expert-level proficiency in Python and/or TypeScript/JavaScript.
- Ability to prototype, debug, review, and contribute code across multiple layers of the technology stack.
- Serve as the highest-level technical authority within the AI Applied Engineering organization.
- Influence organizational outcomes through technical excellence, credibility, and demonstrated results rather than formal authority.
- Balance innovation with operational discipline and long-term sustainability.
- Establish scalable technical standards that enable teams to move faster while maintaining quality and reliability.
- Drive alignment across engineering, product, business, clinical, compliance, and executive stakeholders.
- Build organizational capability by mentoring and developing the next generation of technical leaders.
- Foster a culture of engineering rigor, continuous learning, accountability, and responsible AI development.
- Success in This Role
- Successful candidates are respected technical leaders who combine strategic thinking with hands-on execution. They influence organizations through technical expertise, data-driven decision-making, and working solutions rather than formal authority alone.
- You are energized by difficult, long-horizon problems and are comfortable making high-impact decisions that affect multiple teams and products. You view AI architecture, governance, reliability, and responsible deployment as critical engineering disciplines, not afterthoughts.
- Most importantly, you remain a builder. Your strategies are informed by real experience developing, testing, and operating production systems, and your credibility comes from your continued ability to solve hard technical problems through architecture, experimentation, and code.
- Technology StackTypeScriptReact / Next.jsPythonPostgreSQLGemini on Vertex AIOCR and Document AI technologies
- DockerKubernetesModern CI/CD platforms and tooling
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