AI Solutions Architect

QuilrAI

1d

About The Position

As an AI Solutions Architect, you will serve as a trusted technical advisor to enterprise customers, helping them design and implement secure, scalable AI solutions using Quilr. You will work with customer architects, engineering leaders, platform teams, and security stakeholders to understand their environments, translate business and security requirements into practical architectures, and guide technical evaluations and deployments. Internally, you will partner with Solutions Engineering, Field Development, Sales, Product, and Core Engineering to ensure proposed solutions are technically sound, secure, and achievable.

This is a customer-facing, hands-on architecture role requiring the ability to connect enterprise AI strategy with implementation details and explain technical trade-offs clearly to technical and business stakeholders. The role includes customer discovery and solution design, enterprise AI security architecture, support for technical evaluations and deployments, and cross-functional product collaboration. Candidates must possess active, valid US work authorization; Quilr is unable to provide visa sponsorship.

Requirements

• Typically 5+ years of experience in solutions architecture, software engineering, cloud architecture, cybersecurity, platform engineering, or a related technical field.
• Demonstrated experience designing and integrating enterprise applications, APIs, cloud services, or distributed systems.
• Working knowledge of LLM-powered applications, AI agents, retrieval-augmented generation (RAG), and modern AI application architectures.
• Strong understanding of cloud infrastructure, networking, identity and access management, authentication, authorization, and enterprise integration patterns.
• Ability to design secure, scalable, reliable solutions and explain technical trade-offs to engineering teams and business stakeholders.
• Experience in customer-facing technical consulting, architecture workshops, presales engineering, or technical solution delivery.
• Strong written and verbal communication skills, including the ability to create architecture diagrams, technical proposals, and implementation plans.
• Ability to operate effectively in a fast-paced startup environment with evolving requirements and product capabilities.
• Active, valid US work authorization; visa sponsorship is not available.

Nice To Haves

• Experience in AI security, application security, cloud security, or product security.
• Familiarity with OWASP guidance for LLM applications and agentic AI, threat modeling, AI red-teaming, or penetration-testing methodologies.
• Knowledge of MCP clients, servers, tools, permissions, and trust boundaries.
• Experience with AWS, Azure, or GCP, plus Docker, Kubernetes, API gateways, or service meshes.
• Familiarity with SIEM platforms, secrets management, enterprise identity providers, and security monitoring.
• Experience defining security controls, AI risk-management practices, or governance requirements for enterprise AI deployments.
• Relevant cloud, security, or architecture certifications.

Responsibilities

• Lead technical discovery sessions with customer engineering, cloud, platform, and security teams to understand AI use cases, infrastructure, constraints, and risk requirements.
• Design end-to-end solutions integrating Quilr with enterprise LLM applications, AI agents, orchestration frameworks, data sources, APIs, and MCP-based workflows.
• Translate customer needs into solution architectures, integration patterns, deployment plans, and technical success criteria.
• Create architecture diagrams, technical proposals, implementation roadmaps, and solution documentation tailored to customer environments.
• Build technical champions and trusted relationships with prospects and customers, including meeting face to face.
• Assess AI application architectures and identify risks involving prompt injection, sensitive-data exposure, unsafe tool execution, excessive agent permissions, and untrusted context.
• Design trust boundaries, authentication and authorization patterns, policy enforcement points, secrets-management practices, and audit logging.
• Recommend secure deployment patterns across cloud, private cloud, on-premises, and hybrid environments based on customer requirements and product capabilities.
• Consider reliability, scalability, performance, observability, maintainability, and operational readiness in proposed solutions.
• Support presales activities, technical workshops, architecture reviews, POC planning, and customer technical evaluations.
• Define measurable POC success criteria and help customers validate functionality, security controls, integration feasibility, and operational fit.
• Guide AI Field Developers and Solutions Engineers on implementation decisions, integration dependencies, and complex technical escalations.
• Collaborate with customer teams to resolve architectural blockers and support the transition from evaluation to production deployment.
• Partner with Sales, Product, and Engineering to align customer requirements with Quilr's capabilities and roadmap.
• Capture recurring customer needs, architectural gaps, and field insights and translate them into actionable product feedback.
• Develop reusable reference architectures, implementation patterns, and best practices to improve consistency across customer deployments.
• Communicate technical trade-offs, limitations, risks, and dependencies clearly without overpromising product capabilities.
• Deliver secure, implementable solution architectures; help customers validate technical fit and progress from discovery and evaluation to deployment; build customer trust; reduce repeated implementation effort; and provide actionable field feedback to inform product capabilities and roadmap.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed