AI Integrations Solutions Architect

Our client is a leading global cybersecurity company. Its Digital Transformation Office is building the company's internal AI platform, with an AI-native way of working and security built into everything it ships.

You will own, end to end, how systems connect to the client's core AI platforms. You will set the architecture for MCP servers, agent workflows and data integrations, then take them to production, governed and adopted. This is a senior technical lead role at Principal / Staff level for someone who can both design the target state and deliver it across teams, reporting to the Senior Director of AI Engineering & Architecture.

• A reference architecture and target-state roadmap for AI integrations across Claude, MCP, Snowflake, n8n and core SaaS (Salesforce, Atlassian, Microsoft 365, Slack).

• A single register of every first-party and third-party MCP and agent integration, with owner, data classification, permissions, risk tier and lifecycle status.

• A working release cadence across engineering, security, data platform and go-to-market operations: intake, prioritization, dependencies, release gates, sign-off and reporting.

• A connector evaluation model built into delivery, so approval is a clear path with defined criteria and turnaround, not a bottleneck.

• Two production integrations shipped end to end as proof of the pattern, with measured cost, reliability and adoption.

Architecture

• Set secure, scalable patterns for MCPs, agent orchestration and data access, with least privilege, auditability and containment built in.

• Make and document build, buy or adopt decisions for platforms, infrastructure and third-party connectors.

• Lead design and security reviews, and define reliability, latency, cost and observability standards.

Technical program management

• Own the integration portfolio roadmap, sequencing, capacity, risks and dependencies.

• Turn business demand into prioritized delivery plans with clear scope, acceptance criteria and reporting.

• Manage release readiness, change control, production sign-off, post-implementation reviews and vendor capacity.

Technical leadership

• Stay hands-on: review designs, code and configurations, unblock engineers and prototype when needed.

• Mentor engineers on integration design, evaluation and operational ownership.

• Define quality measures for accuracy, reliability, cost and adoption, with Security, Legal and Data Governance controls built in.

What's out of scope

• Line management: this is technical leadership only.

• Owning the business domain: domain teams own definitions and processes; you own the integration and AI layer.

How the team works

• AI-native: Claude, Claude Code and Cowork are the default way of building.

• Security first: least privilege, auditability and change control apply to everything shipped internally.

• Working in the open: design notes in Confluence, work tracked in Jira and decisions written down.

Claude • MCP • Agent orchestration • Snowflake • n8n • Python • SQL • Salesforce • Atlassian • Microsoft 365 • Slack

Required

• 10+ years across software, data or solutions architecture, including 3+ years leading cross-team technical delivery.

• A proven record designing and shipping production integrations on API, event-driven or agent-based architectures.

• Working knowledge of MCP or comparable tool-calling and agent integration patterns, and the security model around them.

• Strong grounding in identity, access and audit design: OAuth/SSO, least privilege, service accounts and logging.

• Technical program management skills: roadmapping, dependency and risk management, stakeholder reporting and vendor management.

• Strong Python and SQL, enough to review and prototype.

• Experience with a cloud data platform (Snowflake preferred) and enterprise SaaS data models (Salesforce preferred).

• Clear written communication: able to produce a design document, a risk assessment and an executive brief in the same week.

• Advanced English and at least 4 hours of daily overlap with US Eastern Time.

• Workflow and agent orchestration platforms such as n8n or Bedrock AgentCore.

• Enterprise LLM platform governance: usage controls, cost attribution, and model and connector approval.

• A cybersecurity or regulated-industry background.

• Snowflake Cortex (Analyst, Agents, Search) and semantic layer experience.

• Evaluation methods for LLM-powered systems.

• 100% remote role

• Full-time position at Principal / Staff level

• Work on the client's internal AI platform with an AI-native team

• On-site in Medellin with Parking