Engineer
Category-defining tech. Career-defining work.
Lots of tech companies disrupt. But, many fail when they try to scale. We're different. CockroachDB makes it easier for companies to build and scale apps. This is how and why we're helping some of the most innovative companies on the planet. We tackle problems head-on and focus on solutions that create lasting impact. Because when our customers win, we all win. At Cockroach Labs, we believe the path to becoming an AI-native company starts within. We’re embedding AI agents into our workflows to drive productivity, reduce manual overhead, and unlock new ways of working. The AI Solutions Architect will be instrumental in this journey, acting as a technical builder, internal consultant, and cross-functional integrator. This individual will partner with teams across the business to identify high-impact opportunities for automation, build intelligent agentic systems, and help scale adoption of AI across our internal tools and systems. The role will work closely with Corporate IT, Security, and teams across GTM, R&D, and G&A. You Will- Identify and Prioritize Workflow Opportunities: Partner cross-functionally to identify and prioritize internal workflows where AI agents can significantly enhance productivity, starting with GTM automation. Develop a strong understanding of business priorities, system dependencies, and operational bottlenecks to help teams identify the highest-leverage opportunities for AI automation.
- Design and Implement Agentic Systems: Architect and deploy AI-driven solutions using tools such as LangChain, OpenAI, LangGraph, and vector databases, with a strong emphasis on integrating systems and automating workflows through platforms like Zapier or custom APIs. Ensure solutions are tailored to specific business challenges and seamlessly connected across the tech stack.
- Deploy, Scale, and Operationalize AI Agents: Ship agents that live inside our real workflows, Slack threads, GitHub repos, Notion docs, retros, etc. Your agents will act like teammates, not just scripts.
- Enable Reuse and Drive Adoption: Wrap effective agents into internal SDKs, APIs, or interfaces so other teams can build on your work. Lead change management efforts to drive adoption, including documentation, training, and stakeholder enablement to help teams across the business confidently leverage AI in their workflows.
- Define Measurable KPIs: Collaborate with cross-functional stakeholders to establish clear, measurable KPIs aligned with driving internal efficiency. Ensure each team involved has defined success metrics to monitor impact and continuously optimize AI system performance.
- Ensure Secure, Responsible AI Integration: Ensure security, accuracy, and compliance by incorporating guardrails, data governance, compliance, HITL, memory, observability, and prompt testing.
- Act as a Consultant & Architect: Act as an internal consultant and architect, guiding teams on AI system design, feasibility, and best practices. Where external partners are involved (e.g., Dust.tt), provide technical oversight to ensure quality and alignment.
- 7+ years of experience in business systems roles (or related), with experience with LLMs, agent frameworks, or automation systems.
- Strong knowledge of AI technologies and their applications in business systems.
- Proficiency in both declarative configuration (clicks) and custom development (code) to build out AI systems.
- Strong analytical skills to identify system inefficiencies and apply AI solutions to improve performance.
- Demonstrated ability to operate in zero-to-one environments and prioritize effectively across ambiguous, cross-functional contexts.
- Strong business acumen with the ability to proactively identify areas where business systems can be improved, driving innovation and efficiency.
- Experience navigating security, data privacy, and compliance constraints.
- Excellent communication and interpersonal skills to work effectively with internal stakeholders and cross-functional teams.
- Background in ETL, business systems integration, or enterprise tooling.
- Experience managing external consultants or vendors on technical AI projects.
- Contributions to open-source agentic tools or internal platforms.
- Familiarity with AI governance frameworks or responsible AI best practices.
- Prior experience acting as an internal architect or technical advisor across multiple functions.
- Stock Options
- Medical Insurance
- Vision Insurance
- Dental Insurance
- Life and Disability Insurance
- Professional Development Funds
- Flexible Time Off
- Paid Holidays
- Paid Sick Days
- Paid Parental Leave
- Retirement Benefits
- Mental Wellbeing Benefits
- And more!
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