AI Change Architect

Company Overview:

Business Integration Partners (BIP) is Europe’s fastest growing digital consulting company and are on track to reach the Top 20 by 2030, with an expanding global footprint in the US (New York, Charlotte, Chicago, and Houston). Operating at the intersection of business and technology we design, develop, and deliver sustainable solutions at pace and scale creating greater value for our customers, employees, shareholders, and society.

BIP specializes in high-impact consulting services across multiple industries with 6,000 employees worldwide. Our domains include Financial Services business serves Capital Markets, Insurance and Payments verticals, supplemented with Data & AI, Cybersecurity, Risk & Compliance, Change Management and Digital Transformation practices. We integrate deep industry expertise with business, technology, and quantitative disciplines to deliver high-impact results for our clients.

BIP is currently expanding its footprint in the United States, focusing on growing its Capital Markets and Financial Services lines. Our teams operate at the intersection of business strategy, technology, and data to help our clients in driving smarter decisions, reducing risks, and staying ahead in a fast-evolving market environment.

About the Role:

We are seeking an experienced AI Change Architect to lead the design and implementation of an AI-first enterprise architecture centered on autonomous agents and scalable AI platforms. This role will be instrumental in reimagining technology platforms, data workflows, and operating models to enable secure, reliable, and high-performance AI solutions across the organization.

The architect will operate at the intersection of agentic systems, LLM infrastructure, and enterprise platform transformation shaping how capabilities such as RAG pipelines, model orchestration, vector search, and AI workflow automation are designed, governed, and deployed at scale.

The successful candidate combines deep architectural expertise with hands-on AI platform understanding, helping shape how advanced AI systems are implemented across business units from model routing and retrieval architecture to workforce and delivery model evolution. This is a strategic and highly visible role focused on building the future state of large-scale AI-augmented operations.

Key Responsibilities:

• Define and lead the architectural vision for an AI-first enterprise, embedding autonomous agents, LLM services, and intelligent automation across technology and data ecosystems.
• Architect scalable AI platforms supporting model routing, multi-model orchestration, and enterprise AI service delivery across business units.
• Design enterprise RAG architectures, including embeddings strategies, retrieval layers, chunking frameworks, vector search optimization, and latency/performance trade-offs.
• Establish reference architectures for vector databases and semantic search platforms (e.g., Pinecone, FAISS, Milvus, pgvector, Vespa) across cloud and on-prem environments.
• Define retrieval and inference pathways spanning enterprise data platforms, knowledge sources, and AI applications with secure permissioning and governance.
• Partner with data engineering and platform teams to evolve the enterprise data platform to support AI workloads, including embedding pipelines, metadata layers, and human-in-the-loop processes.
• Design scalable strategies for creating, deploying, orchestrating, and governing large populations of autonomous agents and AI workflows.
• Establish and lead an internal “agentic lab” to prototype agent-based and RAG-driven workflows and evaluate emerging AI architecture patterns.
• Define enterprise standards for LLM integration (e.g., OpenAI, Azure AI), inference APIs, and AI service abstraction layers.
• Architect cross-platform automation by integrating internal agents with enterprise systems and native platform AI capabilities.
• Define AI testing, validation, and safety frameworks to ensure robustness, compliance, and reliability of AI deployments.
• Drive next-generation operating models for AI-assisted development, including code generation, QA, release, and governance practices.
• Provide thought leadership on enterprise AI transformation, influencing long-term architecture, operating model, and delivery strategy.

Required Skills and Experience:

• 7+ years of experience in enterprise architecture, AI platform architecture, ML infrastructure, or large-scale …