AI Solutions Engineer - Sales & Marketing AI Systems

At 1Password, we’re building the foundation for a safe, productive digital future. Our mission is to unleash employee productivity without compromising security by ensuring every identity is authentic, every application sign-in is secure, and every device is trusted. We innovated the market-leading enterprise password manager and pioneered Unified Access Management, a new cybersecurity category built for the way people and AI agents work today. As one of the most loved brands in cybersecurity, we take a human-centric approach in everything from product strategy to user experience. Over 180,000 businesses , from Fortune 100 leaders to the world’s most innovative AI companies, trust 1Password to help their teams securely adopt the SaaS and AI tools they need to do their best work.

1Password's Solutions Marketing team is responsible for the stories, use cases, competitive narratives, and go-to-market (GTM) assets that sellers rely on every day. Solutions Marketing is building an AI-native service for Sales . Instead of asking sellers to search static playbooks and personalize assets for each of their accounts themselves, the AI service will create signal-driven guidance, personalized messaging, and always-current content for each selling situation.

You’ll build and operate the internal AI services that help sellers find current market intelligence, create tailored sales assets, and respond to deal signals without relying on static playbooks. This role is responsible for designing, building, and running the agent systems that support sellers across account planning, active deals, campaigns, competitive positioning, and sales enablement. You’ll work with large language model providers , coding agents, retrieval systems, and modern agent frameworks. Current examples include Claude, Codex , and other tools selected for reliability, security, and fit.

This is an internal product engineering role. You’ll treat Sales and Marketing teams as users, build against their real workflows, and turn successful solutions into maintained capabilities that can serve the broader organization.

You’ll sit within Solutions Marketing and work closely with Sales leadership, Marketing Operations, Data, Security, and central IT. You’ll own product and workflow decisions for Solutions Marketing systems while partnering with central IT and Engineering on shared infrastructure, access controls, security reviews, and production operations.

If you've been building with agents, workflows, and production AI systems and want to do it inside a company that ships AI to production, this is that role.

How we’re using AI today

On the Marketing team, we’re growing our AI capability together and redesigning how work gets done. We’ve built agents to improve workflows focused on competitive intelligence, content creation, and campaign planning, helping us stay sharp, reduce context-switching, and surface the right information at the right time. AI helps us coordinate, execute, and uncover insights faster so we can spend more time on what’s most important: performance, judgement, and driving the future of 1Password.

This is a remote opportunity within Canada and the US.

What you will build:

• Discover and define workflows: Work directly with sellers, product marketing managers (PMMs), and campaign managers to map how they work today, where time is wasted, and what good output looks like. Begin with direct observation and conversations with the people doing the work, then turn those insights into clear technical requirements.

• Define the agent runtime and application architecture: Design how the system manages context, state, tools, permissions, retrieval, evaluation, and human review. Define how it ingests account signals and playbook intelligence, routes requests to specialist agents, and surfaces outputs in the tools teams already use.

• Design trusted knowledge flows: Define how the system finds, evaluates, and uses account, persona, product, competitive, and campaign information. Make thoughtful decisions about source-of-truth systems, information freshness, conflicting sources, structured and unstructured data, and provenance.

• Build routing and specialist agents: Build the routing and execution system that selects the right tools, data sources, and specialist agents for each request. Cover sales asset generation, campaign briefs, competitive responses, copy production, and field support for active deals.

• Integrate with Sales AI and go-to-market platforms: Connect the AI layer to the platforms 1Password runs on, including Salesforce, Seismic, Gong, Notion, Snowflake, and Slack . Ensure it works alongside existing Sales AI tools and workflows, with permission-aware tool use and clear boundaries for what each agent can access and change.

• Design for trusted access and safe autonomy: Design and test permission-aware retrieval, source-level authorization, audit trails, provenance capture, prompt injection defenses, retention and deletion controls, and safe handling of customer and account information. Define where agents can act independently, where human approval is required, and how the system records those decisions.

• Evaluate and improve agent behavior: Tune agent behavior using representative evaluation sets, seller feedback, usage data, and output quality signals. Measure accuracy, relevance, consistency, editing effort, adoption, and other workflow-specific outcomes. Improve prompts, tools, retrieval, models, and agent behavior as the go-to-market motion and product landscape evolves.

• Build quality and reliability guardrails: Build evaluation frameworks, regression pipelines, release checks, and escalation paths that keep outputs accurate, useful, on-brand, and consistent. Define how workflows handle uncertainty, failure, and human review. Production output is valuable only when it is trustworthy and useful to the teams receiving it.

• Operate and evolve the system: Own the roadmap and the full lifecycle of the systems you build, from prototype through reliable production use and eventual retirement. Monitor system performance, usage, quality, latency, and cost. Identify what to build next, deprecate what is not working, and partner with the appropriate teams to resolve failures and improve reliability.

How success will be measured:

• Measure time to find relevant account and persona intelligence across defined seller workflows.

• Generated assets take less time to produce and require less manual editing.

• Agent outputs include current sources and clear provenance.

• Track unsupported claims, stale-source usage, citation coverage, and manual editing effort over time.

• Track adoption and repeat usage among defined seller and product marketing manager cohorts.

• Time-to-response, cost-per-request, and output accuracy tracked against defined thresholds for each workflow in production.

What we are looking for:

You have shipped AI-enabled software that real users rely on.

• Production AI systems: 6+ years experience designing, building, and operating workflows that use large language model (LLM) APIs, tool calling, retrieval, structured outputs, and agent workflows . Candidates should be able to describe systems they have shipped, how they evaluated them, what failed, and how they improved them based on real user feedback.

• Agent-system architecture: Experience designing workflows with clear agent boundaries, context and state management, permission-aware tool use, evaluation, observability, failure handling, and human escalation. Familiarity with tools such as Claude, Codex, Cursor, Dust, LangChain, or LangGraph is useful but not required.

• Technical judgment: Choose the simplest reliable approach for the problem. Know when to use deterministic code, a workflow, retrieval, a single agent, multiple agents, or human review. Avoid adding agentic complexity where it does not create meaningful value.

• Builder's instinct: you'd rather put a working prototype in front of a seller today than write a spec about what's theoretically possible next quarter.

• Evaluation: Experience building evaluation frameworks to measure agent output quality through prompt evaluations, output scoring, and regression testing against verified examples.

• User-centered delivery: Prototype quickly with users, learn from real feedback, and turn what works into documented, reliable production systems.

• Cross-functional collaboration: Translate workflow needs and feedback from PMMs, sellers, and campaign managers into clear technical requirements.

• Technical communication: Explain system architecture and technical tradeoffs to engineers, then translate workflow constraints and user feedback into clear decisions with PMMs and sellers.

Preferred Qualifications:

• Go-to-market fluency: Working knowledge of business-to-business software as a service ( B2B SaaS ) marketing and sales workflows, including personas, buying stages, positioning, competitive narratives, campaigns, sales enablement, and content governance. Able to translate feedback from PMMs, sellers, and campaign managers into clear product requirements and measurable improvements.

• Sales, marketing, and data platforms: Familiarity with Seismic, Salesforce, Gong, Notion, Snowflake, or Slack APIs ; experience with integration platform as a service ( iPaaS ) tools for cross-system automation; exposure to B2B SaaS or enterprise go-to-market environments.