AI Architect
Job Location:
Job Location:
Fort Mill, SC - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
16 days ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Role Summary- AI Architect
Fort Mill SC
We are seeking experienced AI Architects to lead the design development and enterprise adoption of AI/GenAI solutions including advanced agentic AI systems across BFS clients.
The role requires strong experience in building production-grade enterprise agentic applications with a focus on scalability performance (sub-2 second response times) and robust observability.
Key Responsibilities
- Define AI architecture strategies aligned with business goals
- Design and implement GenAI / Agentic AI solutions (LLMs copilots autonomous agents) using modern frameworks
- Lead end-to-end AI solutioning (use case design deployment scale)
- Architect microservices-based cloud-native AI platforms
- Develop enterprise-grade agentic systems including:
- Tool invocation and orchestration
- Memory management
- Agentic identity and access control
- MCP gateways and integrations
- Ensure high-performance systems with < 2s response time for production workloads
- Implement observability and monitoring frameworks for AI/agent systems
- Define AI governance security and compliance frameworks
- Collaborate with:
- Business stakeholders
- Domain SMEs
- Engineering & delivery teams
- Drive reuse of AI accelerators and enterprise assets
- Guide teams on MLOps / LLMOps / Prompt Engineering practices
Required Skills
- Core AI & Agentic Stack
- Strong experience in:
- AI/ML GenAI LLMs (OpenAI Claude etc.)
- Agent-based frameworks and ecosystems
- LangChain LangGraph for agent orchestration
- AWS Bedrock for enterprise GenAI solutions
- Development & Architecture
Hands-on knowledge of:
- Python (mandatory) Java (preferred)
- REST APIs microservices architecture
- Experience designing scalable production-grade agent systems
Cloud & Data
Cloud platforms:
AWS (preferred) / Azure / GCP
Experience in:
Vector databases (Pinecone FAISS)
RAG (Retrieval-Augmented Generation) architectures
Enterprise Capabilities
Experience in:
Cloud platforms:
AWS (preferred) / Azure / GCP
Experience in:
Vector databases (Pinecone FAISS)
RAG (Retrieval-Augmented Generation) architectures
Enterprise Capabilities
Experience in:
- Observability integration for AI systems
- Tool calling frameworks and agent orchestration
- Memory handling in agent workflows
- Secure agent identity and access control
- Strong understanding of:
- Security Responsible AI Data Privacy
Experience
- 10 to 15 years overall experience
- Minimum 3 to 5 years in AI/ML/GenAI architecture roles
- Proven experience in building enterprise-scale agentic AI solutions
