We are seeking an Enterprise Architect to lead the design and implementation of an enterprise‑scale, event‑driven action and approval orchestration platform.
This role will define the target application architecture, guide engineering teams, and ensure that the solution is scalable, secure, and aligned with business outcomes.
The ideal candidate has strong experience in enterprise application design, workflow orchestration, and integration‑heavy platforms, with a practical mindset balance between architecture rigor and delivery velocity.
Key Responsibilities :
- Define the end‑to‑end application architecture for the orchestration platform
- Design modular, loosely coupled components
- Ensure alignment with enterprise architecture standards and principles
- Define event‑driven integration patterns (Pub/Sub, async APIs)
- Design canonical data models to normalize inbound requests
- Guide API and webhook patterns for external systems (CRM, ERP, HR, ITSM)
- Ensure extensibility for additional systems and use cases
- Define how AI is embedded into workflows (context enrichment, prioritization)
- Ensure AI acts as decision assist, not autonomous authority
- Design explainability, auditability, and fallback paths
- Align AI usage with enterprise governance and trust requirements
- Work closely with: Product managers Engineering teams AI and data engineers QA and DevOps teams
- Review designs, code, and architectural decisions
- Provide technical leadership during development, testing, and rollout
- Support UAT and production readiness activities
Required Skills & Experience
Core Experience
- 10+ years in application design and development
- 4+ years in an architecture or technical leadership role
- AI/LLM Platform Patterns: Practical experience with multi-agent orchestration, model/embedding selection, RAG pipelines
- Strong experience designing enterprise‑scale platforms
- Microservices and modular application architectures
- Workflow engines / orchestration frameworks (BPM, DAG‑based systems)
- Event‑driven architecture and messaging platforms
- REST and async API design
- Relational and NoSQL data modeling
- Security‑by‑design principles
Good to Have
- Experience with approval or decision‑centric platforms
- Knowledge of domain workflows (Finance, Sales Ops, HR, ITSM)
- Experience delivering MVPs and scaling them to enterprise platforms
- Graph & Query Expertise: SPARQL, SHACL, Gremlin/PGQL; ontology/taxonomy stewardship and data lineage/provenance.
- Evaluation Tooling: Experience with LLM evaluation harnesses (e.g., custom scoring frameworks, judge models, A/B test rigs), regression dashboards, and automated re-eval pipelines.
- Model & Tooling Ecosystem: Familiarity with OpenAI, open-weights (Llama/Mistral), and connector protocols (e.g., MCP-style adapters).
- Runtime & Infra: Service mesh (Istio/Linkerd), API gateways, Kafka/event streaming, feature flags, multi-tenancy, and cost governance for model/runtime spend.
- Security & Compliance: Exposure to SOC 2/ISO 27001 (or comparable) practices; prompt-injection mitigation and data-exfiltration controls for LLMs.
- Languages & Stacks: Proficiency in one or more: Python, TypeScript/Node.js; comfortable reading/writing infra and application code to produce reference blueprints.
- UX & HITL Patterns: Designing clear approval flows and rationale/explanation UX for human-in-the-loop actions.
This role is ideal for a hands-on architect who can set a clear architectural runway, codify patterns, and steer multiple teams toward secure, explainable, and cost-effective AI capabilities at enterprise scale.