Solution Architect AI Gateway & Intelligence Platform - Austin, TX (Hybrid)

Solution Architect - AI Gateway & Intelligence Platform

Position: Contract

Location: Austin, TX | Charlotte, NC | New York, NY | Tempe, AZ | San Diego, CA (Hybrid)

Duration: 12+ months

Client: Altimetrik / LPL Financial

Job description:

While the API Architect owns the core gateway architecture, runtime topology, and baseline patterns, this role focuses on:
• AI-aware gateway capabilities
• Policy-driven AI access and governance
• Advanced exposure patterns for AI/LLM-backed APIs
• The intersection of AI, security, and developer experience at the gateway layer
The goal: deliver AI-enabled APIs that are safe, scalable, compliant, and developer-friendly - without fragmenting or duplicating the core API platform.

AI Gateway Solution Architect (This Role)
• Owns AI-specific gateway patterns and capabilities
• Designs how AI models, agents, and services are exposed through Kong
• Defines AI governance controls enforced at the gateway
• Extends (not forks) the core gateway architecture
Success requires strong architectural partnership, shared standards, and disciplined alignment.

Core Responsibilities

AI Gateway Architecture & Design
• Design AI/LLM-backed service exposure patterns through Kong
• Implement policy-based routing, throttling, and traffic controls for AI workloads
• Enforce token, cost, and usage governance at the gateway layer
• Ensure all AI extensions reuse and build upon core Kong patterns
Architectural Collaboration
• Co-author reference architectures and design standards with the API Architect
• Review cross-boundary API + AI designs
• Serve as a bridge between API platform, AI governance, and security
AI Governance by Design
• Translate enterprise AI governance into enforceable gateway policies
• Ensure AI traffic is:
• Auditable
• Rate-limited
• Authenticated and authorized
• Automate governance controls aligned to landing zone guardrails
Developer Experience
• Ensure AI-enabled APIs feel like a natural extension of the existing API platform
• Define onboarding patterns, documentation standards, and self-service workflows
• Prevent AI capabilities from becoming one-off special cases
Required Experience

Platform & Gateway Expertise
• 10+ years designing large-scale distributed systems in enterprise environments
• Deep API platform architecture experience:
• AuthN/AuthZ
• Traffic shaping & rate limiting
• Policy enforcement
• Zero Trust patterns
• Strong hands-on experience with Kong Enterprise, ideally including:
• Kong AI Gateway
• Multi-environment or hybrid deployments
• Custom plugins or policy extensions
• Cloud-native expertise:
• AWS
• Kubernetes
• Infrastructure-as-Code (Terraform or equivalent)
• CI/CD for platform services
AI & LLM Systems Experience
• Hands-on experience designing systems around LLMs and AI-backed services
• Experience operating LLM-backed APIs in production
• Practical understanding of:
• Token-based cost models
• Latency & rate limits
• Probabilistic outputs & guardrails
• Model lifecycle and versioning
• Ability to enforce AI policy and safety controls before traffic reaches models
Governance & Regulated Environment Experience
• Experience designing platforms in regulated environments (financial services preferred)
• Proven ability to translate:
• Security requirements
• Risk controls
• Compliance needs
• into automated platform capabilities
• Experience partnering with:
• Cybersecurity
• Risk & Compliance
• Enterprise Architecture
• Familiarity with responsible AI, model risk, auditability, and governance frameworks
Architecture Leadership
• Experience operating in shared-ownership architectural models
• Ability to define clear boundaries and prevent duplication
• Comfortable influencing without direct authority
• Strong executive communication skills (VP/SVP-level engagement)
• Skilled in writing:
• Architecture Decision Records (ADRs)
• Reference architectures
• Technical narratives
Platform Mindset

You think of platforms as products, with:
• Clear developer users
• Opinionated defaults
• Measurable adoption and safety outcomes
You can balance:
• Flexibility vs. standardization
• Speed vs. safety
• Innovation vs. governance
• And you design solutions that scale across domains-not just single use cases.
• Ability to demonstrate technical concepts to non-technical audiences

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