Job Description
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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