AI Consultant -AI Integration consultant

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We are looking for a Senior AI Integration Consultant to establish a practical blueprint for integrating Databricks-hosted AI services, primarily using OpenAI models, into legacy credit underwriting workflows.

The consultant must combine solution architecture expertise with hands-on experience in AI service integration and be able to deliver an actionable target architecture, integration patterns, roadmap, and pilot recommendation within three months.

Core requirements

- Proven experience designing integration blueprints for embedding AI services into existing enterprise workflows and legacy applications.

- Strong solution architecture skills, including API-based integration, event-driven patterns, orchestration, authentication, data flows, and system dependencies.

- Hands-on experience with Databricks, including its use as a platform for deploying and operationalizing AI or data services.

- Practical experience integrating LLM-based services, such as Azure OpenAI models, into production business processes.

- Experience translating standalone AI solutions into reusable enterprise services, with clear interfaces, service boundaries, and integration patterns.

- Ability to assess current-state architecture and define a pragmatic target-state blueprint, including transition steps, dependencies, constraints, and implementation priorities.

- Experience working with complex workflow or case-management applications, preferably within credit underwriting, financial services, banking, or vendor finance.

- Strong understanding of enterprise non-functional requirements, including security, privacy, access management, auditability, monitoring, resilience, and scalability.

- Ability to work across AI development, business, architecture, security, data, and application teams, converting business journeys into implementable technical designs.

- Delivery-oriented consulting approach, with the ability to produce actionable outputs within three months, including architecture diagrams, integration patterns, implementation roadmap, and recommendations for a first integration pilot.

- Experience defining and documenting reusable integration patterns and service interfaces that can be leveraged across multiple business processes and applications.

- Ability to identify and assess technical dependencies, legacy system constraints, and integration challenges impacting AI adoption.

- Experience developing transition roadmaps from current-state to target-state architecture, including implementation priorities and sequencing.

- Proven ability to recommend and design an initial AI integration pilot that delivers measurable business value and supports broader enterprise adoption.

De eisen

- 1Proven experience designing integration blueprints for embedding AI services into existing enterprise workflows and legacy applications.

- 2Strong solution architecture skills, including API-based integration, event-driven patterns, orchestration, authentication, data flows, and system dependencies.

- 3Hands-on experience with Databricks, including its use as a platform for deploying and operationalizing AI or data services.

- 4Practical experience integrating LLM-based services, such as Azure OpenAI models, into production business processes.

- 5Experience translating standalone AI solutions into reusable enterprise services, with clear interfaces, service boundaries, and integration patterns.

- 6Ability to assess current-state architecture and define a pragmatic target-state blueprint, including transition steps, dependencies, constraints, and implementation priorities.

- 7Experience working with complex workflow or case-management applications, preferably within credit underwriting, financial services, banking, or vendor finance.

- 8Strong understanding of enterprise non-functional requirements, including security, privacy, access management, auditability, monitoring, resilience, and scalability.

- 9Ability to work across AI development, business, architecture, security, data, and application teams, converting business journeys into implementable technical designs.

- 10Delivery-oriented consulting approach, with the ability to produce actionable outputs within three months, including architecture diagrams, integration patterns, implementation roadmap, and recommendations for a first integration pilot.

- 11Experience defining and documenting reusable integration patterns and service interfaces that can be leveraged across multiple business processes and applications.

- 12Ability to identify and assess technical dependencies, legacy system constraints, and integration challenges impacting AI adoption.

De wensen

- 1Experience developing transition roadmaps from current-state to target-state architecture, including implementation priorities and sequencing.

- 2Proven ability to recommend and design an initial AI integration pilot that delivers measurable business value and supports broader enterprise adoption.