Application Architect - AI Integration

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success.

You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

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. The Application Architect collaborates with stakeholders to translate business objectives into scalable designs, balancing vendor-managed services with custom development, and drives governance for AI integration.

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.

Bachelor's Degree

• - 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/Event Bridge), 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, Sage Maker)
• - Data architecture experience — OLTP/OLAP separation, CDC patterns, data domain ownership, master data management, and real-time vs. batch pipeline design

• - Hands-on architecture experience designing systems that embed AI capabilities — RAG pipelines, LLM orchestration (Lang Chain, Llama Index, 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 constraints

• - 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 concerns

• - Demonstrated ability to drive architecture decisions through ambiguity —…