Vista previa de la oferta
Principal Software Engineer-AI
lead · Technology / Software Development
Skills and Competencies- 12+ years of software engineering experience, including 5+ years leading engineering teams and delivering complex, large-scale, multi-team initiatives with measurable business impact
- Experience leading multiple teams or groups of teams, including managing engineering managers, technical leads, and staff-level engineers with accountability for delivery outcomes across a portfolio
- Strong technical depth in TypeScript, Python, C#, or similar technologies, with the ability to engage credibly in architecture and code reviews, challenge design decisions, and assess technical risk
- Deep expertise in enterprise AI applications built on large language models, including agents, retrieval augmented generation, orchestration frameworks, model optimization, and evaluation frameworks
- Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling)
- Experience running AI systems in production at scale, including observability, cost and capacity planning, regression detection, and incident response for AI-powered applications
- Experience operating production distributed systems on AWS/Azure, with a strong grasp of reliability, observability, and incident response at scale
- Deep knowledge of cloud-native technologies, serverless applications, event-driven architectures, data and inference pipelines, relational, NoSQL, and vector databases, and modern software architecture patterns
- Proven track record of owning multi-year technical strategy and architectural roadmaps, guiding teams from AI prototype through production deployment, and influencing organizational change
- Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization
- Bachelor's or master's degree in Computer Science, Engineering, Artificial Intelligence, or a related discipline, or equivalent professional experience
- Define and execute long-term technical strategies while owning the multi-year architecture and technology roadmap for AI platforms and applications
- Lead, grow, and organize multiple engineering teams, including engineering managers, technical leads, and staff-level engineers, with accountability for delivery outcomes across the portfolio
- Drive architectural decisions, organizational alignment, and integration of AI-powered solutions using large language models, retrieval augmented generation, orchestration frameworks, and agentic workflows
- Establish engineering excellence through architecture reviews, code reviews, automated testing, observability, security standards, operational excellence, and machine learning operations practices
- Own budget planning and cost management, including headcount, cloud infrastructure, model consumption, tooling investments, vendor relationships, and build-versus-buy decisions
- Partner with product, business, risk, legal, compliance, and audit stakeholders to maximize customer value and implement responsible AI governance practices
- Attract, develop, and retain engineering talent through mentoring, succession planning, performance coaching, and the cultivation of future engineering leaders
- Define and report on key metrics that demonstrate platform adoption, delivery performance, reliability, cost efficiency, and measurable business impact