About the Role:
We are hiring a client-facing Principal Solution Architect to turn customer problems into production-grade agentic AI solutions on our platform. You will sit between our clients and our engineering and product teams: you scope the use case, design the agent architecture, prove it works, and guide it into production. As a principal, you own our most strategic and complex accounts, set the technical standards for how agentic solutions are built, and raise the bar for the whole solutions team. This role suits someone who can whiteboard a multi-agent workflow with a CTO in the morning and debug a tool-calling failure with an engineer in the afternoon.
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What You'll Do:
Client Engagement and Discovery
- Lead technical discovery with client stakeholders, from executives to engineering teams, to identify high-value use cases for agentic AI.
- Qualify use cases for feasibility, data readiness and risk, and say no to the ones that won't work.
- Act as the trusted technical advisor through pre-sales, pilot and rollout; run workshops, demos and architecture reviews.
- Translate business processes into agent workflows clients can understand and sign off on.
Solution Design and Architecture
- Design end-to-end agentic solutions: agent roles, orchestration patterns (single-agent, multi-agent, human-in-the-loop), tool and API integrations, memory and retrieval (RAG), and guardrails.
- Integrate the platform with client systems: identity (SSO/OAuth), data sources, CRMs/ERPs, ticketing tools and internal APIs, including via MCP or similar tool protocols.
- Make deployment decisions across cloud, VPC and on-prem, covering security, data residency, cost and latency.
- Produce clear architecture documents, solution proposals and statements of work.
- Build proofs of concept and pilots hands-on: prompts, tools, agent configurations and integration code.
- Define evaluation criteria with the client and set up evals for accuracy, reliability, safety and cost before go-live.
- Guide delivery teams and client engineers through production rollout, observability and ongoing tuning.
- Troubleshoot agent behaviour in production: tool-call failures, hallucinations, latency and cost overruns.
Shape the Platform
- Feed field insight back to product and engineering: feature gaps, recurring integration patterns, failure modes.
- Create reusable assets: reference architectures, solution templates, connectors and playbooks.
- Represent the company at client events, webinars and technical briefings.
Technical Leadership
- Own the technical relationship with C-level and VP stakeholders on strategic accounts, including executive briefings and multi-year AI roadmaps.
- Set architecture standards, design review practices and delivery methodology for agentic solutions across the solutions team.
- Mentor and coach senior and mid-level solution architects; lead design reviews and act as the escalation point for the hardest technical problems.
- Partner with sales and product leadership on large, multi-workstream deals: solution strategy, pricing inputs and risk assessment.
What You'll Bring:
- 12+ years in software engineering, solution architecture, forward-deployed engineering or technical consulting, with at least 5 years in senior client-facing architecture roles on enterprise accounts.
- Hands-on work with LLM applications, including agentic systems you have taken to production at enterprise scale: prompt engineering, function/tool calling, RAG, and agent frameworks (e.g. LangGraph, CrewAI, AutoGen, Claude Agent SDK, OpenAI Agents SDK, or in-house equivalents).
- Strong coding ability in Python and/or similar languages; comfortable building integrations against downstream APIs.
- Solid grounding in cloud architecture (AWS, Azure or GCP), containers, networking and enterprise security (SSO, RBAC, secrets, data privacy).
- Excellent communication: you can explain trade-offs to non-technical executives and write architecture docs engineers’ trust.
- Track record of leading large, multi-stakeholder engagements end to end, and of influencing executive decisions without formal authority.
- Experience mentoring architects or engineers and setting technical direction across a team.
Nice to Have:
- Production deployments of multi-agent or long-running autonomous workflows.
- Experience with Model Context Protocol (MCP), vector databases, and workflow engines.
- Background in regulated industries such as financial services, government, healthcare or energy.
- Experience deploying solutions in sovereign, private-cloud or on-prem environments.
- Familiarity with AI governance and risk frameworks.
- Degree in Computer Science, Engineering or a related field, or equivalent experience.
Why the company:
- Mission-Driven Work: Work on cutting-edge AI applications with a talented and passionate team, solving real-world challenges in critical sectors.
- Unparalleled Opportunity: This is a chance to innovate and solve real-world challenges using AI at a company with unique access to world-leading models and resources.
- Career Growth: We offer competitive compensation, benefits, and significant career growth opportunities as a foundational member of the team.
- World-Class Environment: Enjoy a flexible working environment and the latest tools & technologies needed to do your best work.
