Staff AI Architect

Job not on LinkedIn

🔥 0 minutes ago

🍂 Massachusetts – Remote

🍂 Massachusetts – Remote

💵 $191.2k - $239k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

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DigitalOcean

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

☁️ SaaS

SaaS • Cloud Computing

DigitalOcean is a cloud infrastructure provider that offers a suite of products and services for developers to build, deploy, and scale applications. Their platform provides comprehensive tutorials, reference material, and support documentation to assist users in managing resources effectively using their API and CLI tools. With features like Droplets (virtual machines), managed databases, Kubernetes, and a marketplace for third-party applications, DigitalOcean focuses on simplicity and performance. They cater to both individual developers and larger organizations looking for cloud solutions that are easy to implement and manage.

📋 Description

• Own the AI reference architecture, including orchestration, tool use, capability boundaries, memory and state, retrieval, evaluation, and observability • Design, prototype, code, and publish reference implementations for difficult and ambiguous components • Architect shared internal AI platform services for model access, routing, runtimes, evaluation, durable orchestration, and self-service developer experience • Define versioned, schema-defined agent tools and capability layers using standards such as Model Context Protocol • Establish integration, identity, and authorization patterns for safe agent interaction with enterprise systems • Re-architect finance, recruiting, sales operations, support, and IT workflows to be AI-native • Design governance and safety into the architecture, including capability boundaries, human approval, evaluation evidence, audit trails, and lifecycle management • Own unit economics through model routing, context management, caching, batching, and cost attribution • Write RFCs and ADRs, maintain durable interfaces, and define technical standards for AI development, deployment, and operations • Set the technical bar through architecture reviews and high-leverage code; mentor engineers across the US and India • Partner with platform engineering, security, identity, data, program management, and business stakeholders

🎯 Requirements

• Substantial experience as a software, solution, or enterprise architect, typically 10+ years, including ownership above a single project or team • Recent production experience building LLM and agentic systems • Experience with agent orchestration frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI Agents SDK, or equivalents • Experience with Model Context Protocol tooling, retrieval, vector stores, and LLMOps • Experience with evaluation-first development, prompt and agent versioning, regression testing, observability for non-deterministic outputs, and cost attribution • Depth in at least one production language: Python, Go, TypeScript, or Java • Experience with cloud-native infrastructure, including Kubernetes, serverless, APIs, event-driven patterns, and observability • Experience architecting and integrating enterprise systems such as Workday, Salesforce, NetSuite, Greenhouse, ServiceNow, or similar • Experience with API and event-driven design, workflow and iPaaS platforms, and cloud data platforms • Knowledge of agent identity and security, including short-lived machine identity, scoped secrets, delegation with provenance, default-deny tool access, prompt-injection defense, and audit trails • Familiarity with the OWASP Agentic AI risk landscape • Fluency with NIST AI RMF, ISO/IEC 42001, and the EU AI Act • Ability to translate ambiguous business problems into well-bounded AI systems • Excellent written and verbal communication and ability to influence technical and non-technical stakeholders • Effective distributed collaboration across time zones, including with engineering teams in India • Comfortable in a remote environment; the posting also references the Boston/Cambridge community • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience is listed under 'Bonus Points' and is therefore optional

🏖️ Benefits

• Reimbursement for relevant conferences, training, and education • Access to LinkedIn Learning's 10,000+ courses • Employee Assistance Program • Local Employee Meetups • Flexible time off policy • Competitive array of benefits, varying based on local regulations and preferences • Bonus opportunity based on company and individual performance • Equity compensation for eligible employees, including equity grants upon hire • Option to participate in the Employee Stock Purchase Program