What are the responsibilities and job description for the Agentic AI Lead / Architect position at Global Business Ser. 4u?
Key Responsibilities
- Lead the architecture, design, and implementation of enterprise-grade Agentic AI platforms and applications.
- Build and deploy autonomous AI agents leveraging LLMs, RAG, multi-agent orchestration frameworks, and workflow automation.
- Design scalable, secure, and highly available AI solutions on AWS cloud services.
- Collaborate with business stakeholders, clients, product teams, and engineering teams to translate business requirements into AI-driven solutions.
- Define architecture patterns, best practices, governance, monitoring, and AI observability standards.
- Drive technical decision-making across AI/ML, cloud infrastructure, vector databases, and agent frameworks.
- Mentor and guide engineering teams through solution design, development, deployment, and optimization.
- Lead client discussions, technical workshops, architecture reviews, and executive presentations.
- Ensure AI solutions meet enterprise standards for security, compliance, scalability, and performance.
- Stay current with emerging trends in Generative AI, Agentic AI, LLMs, and cloud-native architectures.
- 10 years of overall software engineering experience with at least 3 years in AI/ML or Generative AI solution architecture.
- Strong proficiency in Python with experience building scalable AI applications.
- Deep expertise in AWS services including Lambda, ECS/EKS, Bedrock, SageMaker, API Gateway, DynamoDB, S3, CloudWatch, and related cloud-native services.
- Proven experience designing and delivering at least one production-grade Agentic AI platform in an enterprise environment.
- Hands-on experience with:
- Large Language Models (OpenAI, Claude, Llama, Bedrock Models, etc.)
- Agentic AI frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel, LangChain)
- RAG architectures and vector databases
- Prompt engineering, AI evaluation, and observability
- API design and microservices architecture
- Strong knowledge of software architecture, distributed systems, and scalable application design.
- Experience leading technical teams and driving architecture governance.
- Excellent communication, stakeholder management, and client-facing presentation skills.