AI Architect

Job Description 
Overview 
We are seeking a Senior AI Engineer to define and drive the end-to-end engineering of an 
enterprise-grade agentic orchestration capability that enables smart AI agents to 
autonomously execute workflows, collaborate with humans, and operate securely with 
governed access. This role owns the technical direction and delivery of core capabilities 
spanning agent workflow development environments, automated CI/CD and safe migration 
patterns, human–agent collaboration and long-running orchestration, and agent 
identity/registry/marketplace with policy enforcement. You will serve as the technical 
authority—establishing standards for reliability, auditability, security, and performance; 
driving cross-team execution; and ensuring adoption at scale through enablement and strong 
operational practices. 
Responsibilities 
1) Technical Direction, Architecture Standards & Roadmap Ownership (30%) 
• Define reference architecture, design standards, and engineering guardrails for agent 
workflow orchestration, human collaboration, and identity/governance 
capabilities. (Decide/Consult) 
• Own sequencing of releases, deprecation strategy, and compatibility standards to enable 
safe evolution with minimal disruption. (Decide) 
2) Secure-by-Design Identity, Policy Enforcement & Auditability (25%) 
• Establish and enforce non-human identity patterns, consent propagation mechanisms, 
RBAC/ABAC policy models, and least-privilege access across agent 
workflows. (Decide/Consult) 
• Ensure end-to-end auditability for agent actions, prompt/tool changes, model switches, 
handoffs/messages, approvals, and access decisions; define evidence requirements for 
compliance. (Decide/Consult) 
• Define and enforce data classification, PII redaction, retention/purge, and policy-based 
routing to compliant models/providers. (Decide/Consult) 
3) Deterministic Human–Agent Collaboration & Long-Running Orchestration (20%) 
• Define and drive implementation of deterministic handoff patterns (assign/escalate/co
pilot/co-author), resilient messaging, and stateful long-running workflows with timers and 
compensation/rollback. (Decide/Consult) 
• Ensure seamless integration into enterprise systems (CRM/ITSM/custom apps) via 
gateways and standardized interfaces. (Consult/Decide) 
4) Automated Delivery, CI/CD Gates & Safe Migration Patterns (15%) 
• Define promotion gates and automated CI/CD standards including versioning, testing, 
security scans, approvals, and drift detection. (Decide/Consult) 
• Drive safe migration practices between model providers/versions with minimal downtime 
and proven rollback; define operational playbooks. (Decide/Consult) 
5) Operational Excellence, Reliability & Enablement (10%) 
• Own SLIs/SLOs and operational posture: observability standards (metrics/logs/traces), 
incident and credential compromise runbooks, and release readiness 
reviews. (Decide/Consult) 
• Deliver enablement: reference implementations, developer playbooks, training for platform 
ops and application teams; mentor senior and junior engineers. (Consult/Execute) 
 
Decision-Making Autonomy: High — accountable for architecture standards, cross-team technical 
tradeoffs, governance posture, and operational readiness decisions.Supervision Required: Low — 
operates with periodic alignment to senior leadership and governance forums.Complexity of Role: Very 
high — enterprise-grade orchestration with strict security/audit requirements, multi-tenant isolation, 
deterministic workflow needs, and latency SLOs across multiple integrated systems.Cross-Functional 
Interactions: Yes — leadership-level engagement across security/identity, DevX, SRE, enterprise 
applications, and business/product stakeholders. 
 
Qualifications 
Key Skills/Experience Required Minimum Qualifications: 
  
Minimum Qualifications 
• Bachelor’s in CS/AI/ML/Data Science or equivalent experience required. 
• Master’s preferred 
• 10 year experience in ML, Data Science, AI required. 
• Extensive experience designing and operating enterprise platforms/services with 
production reliability and governance requirements. 
 
Required Expertise 
• Systems/platform architecture: multi-tenant isolation, scalability, versioning, 
backward compatibility, release sequencing 
• Orchestration and workflow systems: Temporal-class systems (or equivalent) 
including long-running workflows, compensation, state persistence 
• Identity and security architecture: SSO (SAML/OIDC), non-human identity, 
RBAC/ABAC, consent propagation, secrets/keys rotation, least-privilege design