What are the responsibilities and job description for the Agentic AI Architect position at Vantage Point Consulting Inc.?
Job Title: Agentic AI Architect
Location: Atlanta, GA/Richmond, VA (Hybrid)
Duration: Long Term
Job Description:
- We are seeking an experienced Agentic AI Architect to design and implement intelligent autonomous systems powered by Large Language Models (LLMs) and advanced AI frameworks.
- The ideal candidate will be responsible for architecting AI agents that can reason, plan, and perform tasks autonomously across enterprise platforms.
- You will work closely with engineering, data science, and product teams to build scalable AI-driven solutions, agent orchestration frameworks, and automation systems.
Key Responsibilities:
- Design and develop Agentic AI architectures using LLM-based frameworks and multi-agent systems.
- Build and deploy autonomous AI agents capable of reasoning, decision-making, and task execution.
- Develop AI workflows using frameworks such as LangChain, AutoGen, CrewAI, or similar agent frameworks.
- Integrate LLMs (OpenAI, Anthropic, Azure OpenAI, or open-source models) into enterprise applications.
- Design API-driven architectures to integrate AI agents with enterprise systems, CRMs, ERPs, and cloud services.
- Implement prompt engineering, RAG (Retrieval-Augmented Generation), and vector databases for knowledge retrieval.
- Collaborate with data engineers and ML teams to deploy scalable AI solutions on cloud platforms (AWS, Azure, or GCP).
- Build secure, scalable, and reliable AI systems with strong governance and monitoring.
- Optimize AI agent performance, latency, and cost efficiency.
- Stay updated with emerging technologies in Generative AI, Agentic AI, and LLM ecosystems.
Required Skills:
- Strong experience with Generative AI, LLMs, and AI agent frameworks.
- Experience designing Agentic AI systems or autonomous AI workflows.
- Hands-on experience with Python, APIs, and microservices architecture.
- Knowledge of LangChain, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.
- Experience with vector databases (Pinecone, Weaviate, FAISS, Chroma).
- Strong understanding of RAG pipelines and prompt engineering.
- Experience integrating AI with enterprise platforms and APIs.
- Knowledge of cloud platforms (AWS, Azure, or GCP).
- Experience with Docker, Kubernetes, and CI/CD pipelines.