Lead AI Architect

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & Dev Ops, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our Fin Labs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more.

Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 16,700+, and has 57 offices in 22 countries within key global markets.

As a Lead AI Architect
, your challenge is to define and drive the enterprise AI strategy, architecture, and implementation roadmap across mission-critical business applications. You will lead the design and delivery of scalable Artificial Intelligence, Generative AI, Machine Learning, and Agentic AI solutions while collaborating with business stakeholders, product owners, data scientists, engineers, and enterprise architects. Leveraging expertise in LLMs, Generative AI, AI/ML platforms, Cloud Technologies, Data Architecture, MLOps, Vector Databases, RAG Frameworks, and AI Governance
, you will help deliver innovative, secure, and high-performing AI solutions that drive business transformation and operational excellence.

The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Charlotte, NC is $120k - $130k/year & benefits (see below).

• Minimum 12+ years of technology experience with at least 5+ years in AI/ML Architecture and Leadership roles
  .
• Strong expertise in designing and implementing Artificial Intelligence, Machine Learning, and Generative AI solutions
  .
• Hands-on experience with Large Language Models (LLMs) including OpenAI, Azure OpenAI, Claude, Gemini, Llama, or Mistral.
• Strong knowledge of Agentic AI, AI Agents, Model Context Protocol (MCP), Multi-Agent Systems, and AI Orchestration frameworks
  .
• Experience building enterprise AI solutions using Lang Chain, Lang Graph, Semantic Kernel, CrewAI, Auto Gen
  , or similar frameworks.
• Expertise in designing and implementing Retrieval Augmented Generation (RAG) architectures.
• Strong understanding of Vector Databases such as Pinecone, Weaviate, Chroma, Milvus, or FAISS.
• Hands-on experience with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Strong knowledge of MLOps, AI model lifecycle management, CI/CD, monitoring, and deployment frameworks.
• Experience designing scalable data architectures supporting AI and analytics workloads.
• Strong programming experience with Python and familiarity with modern software engineering practices.
• Experience implementing AI governance, responsible AI, security, privacy, and compliance controls.
• Strong understanding of distributed systems, APIs, microservices, and cloud-native architectures.
• Experience leading architecture reviews, technical design sessions, and enterprise modernization initiatives.
• Ability to translate business requirements into strategic AI roadmaps and technical solutions.
• Experience working in Agile/Scrum environments and leading cross-functional teams.
• Exceptional leadership, stakeholder management, communication, and presentation skills.
• Banking and Financial Services domain experience is highly preferred.

• Lead the enterprise AI architecture strategy across Generative AI, Machine Learning, Predictive Analytics, and Agentic AI initiatives.
• Define architectural standards, frameworks, and best practices for AI solution development and deployment.
• Design scalable AI platforms and reference architectures to support enterprise-wide AI adoption.
• Architect and implement Gen AI use cases utilizing LLMs, RAG, vector databases, AI agents, and enterprise data sources.
• Lead AI solution design workshops with business stakeholders, product teams, and technical leadership.
• Provide technical leadership and mentorship to AI engineers, data scientists, architects, and development teams.
• Evaluate emerging AI technologies and frameworks and recommend strategic adoption opportunities.
• Develop AI governance, security, compliance, and responsible AI frameworks to ensure enterprise standards are met.
• Oversee AI model lifecycle management including development, deployment, monitoring, and optimization.
• Collaborate with cloud, data, security, and application teams to ensure seamless AI solution integration.
• Drive implementation of MLOps and AIOps practices to improve delivery efficiency and operational reliability.
• Review solution…