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Application Architect - AI Integration
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What they do
A Software Architect develops and defines the architecture for computer software and applications projects. Oversees the entire software development process; may manage projects for multiple clients. Analyzes customer or user needs, defines system architecture, and leads team of software developers to design programs and build applications.
$139,882 / year median in North Carolina
-6% projected decline
Job Description
- Introduction
- A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide.
- Your role and responsibilities
- As an Application Architect for AI Integration, this role is responsible for designing and governing end-to-end architectures that embed AI capabilities into enterprise applications and workflows.
Your primary responsibilities will include:
Designing Architectures:
defining reference patterns for AI services, models, and orchestration layers to integrate seamlessly with existing systems, APIs, and data platforms.- Collaborating with
Stakeholders:
translating business objectives into scalable, resilient, and policy-compliant designs, ensuring performance, security, compliance, and cost objectives are met.Governing AI Integration:
driving governance for prompts, guardrails, and lifecycle management, ensuring observability, privacy, and responsible AI principles are embedded from design through operations.- Required technical and professional expertise
- Core Architecture
- 12+ years of enterprise application architecture experience, with at least 3 years in a lead or principal architect role owning cross-domain target-state design
- Proven experience defining microservices, event-driven (Kafka/SQS/EventBridge), and API-first architectures at scale — including versioning, lifecycle governance, and breaking-change management
- AWS cloud architecture (Solutions Architect Professional or equivalent depth) — EKS, RDS/Aurora, API Gateway, Lambda, SQS/SNS, MSK, and AI/ML services (Bedrock, SageMaker
- Data architecture experience —
OLTP/OLAP
separation, CDC patterns, data domain ownership, master data management, and real-time vs. batch pipeline designAI & Agentic Architecture- Hands-on architecture experience designing systems that embed AI capabilities — RAG pipelines, LLM orchestration (LangChain, LlamaIndex, or equivalent), and agentic workflow patterns
- Experience integrating AI/ML models into production enterprise systems — not just proof-of-concept — including model serving, prompt governance, output guardrails, and cost/latency management
- Familiarity with AI governance frameworks — responsible AI principles, explainability requirements, audit trails for AI-assisted decisions — particularly in regulated industries
- Experience evaluating and selecting AI services (managed APIs vs. self-hosted models) based on data privacy, compliance, and total cost of ownership constraintsDomain & Regulatory
- Financial services or insurance domain experience — understanding of policy lifecycle, commission structures, agent licensing, or carrier integration is strongly preferred
- Experience designing systems that operate under regulatory frameworks —
FINRA, FSRA, SOC
2, GLBA, CCPA, or equivalent — with audit logging, data retention, and access control as first-class architecture concernsTechnical Leadership- Demonstrated ability to drive architecture decisions through ambiguity — producing clear documentation, facilitating design reviews, and building consensus across engineering and business stakeholders
- Experience working in Agile/scaled delivery environments — integrating architecture practice into sprint cadence without becoming a bottleneck
- Track record of mentoring senior engineers and establishing architecture standards that teams adopt and maintain
- Preferred technical and professional experience
- Experience with agent/broker distribution platforms, MLM commission hierarchies, or multi-carrier insurance marketplaces
- Familiarity with ACORD standards, NIPR/Sircon integrations, or DTCC financial messaging
- Experience with Valkey/Redis, Kafka, or distributed caching architecture in high-availability Kubernetes environments
- Prior experience in a consultancy or systems integrator context — ability to operate as a trusted advisor alongside a client engineering teamIBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer.