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AI/ML Engineering
Agentic AI Solutions Architect
Work Experience6+ Years
LocationRemote / Hybrid – EST Hours
EmploymentFull Time
Role Overview
Seeking an experienced Agentic AI Solutions Architect to design and oversee enterprise-grade multi-agent AI systems and autonomous workflow solutions. The role involves architecting scalable AI ecosystems, defining agent orchestration strategies, integrating LLM frameworks, and aligning AI-driven automation solutions with business objectives across industries such as Finance, Healthcare, and Energy.
Responsibilities
- Design end-to-end agentic AI architectures for complex enterprise use cases and autonomous workflows.
- Define multi-agent orchestration strategies, memory frameworks, reasoning flows, and tool integration patterns.
- Architect and implement LLM-powered systems using frameworks such as LangChain, LangGraph, and RAG pipelines.
- Evaluate and select appropriate AI models, vector databases, orchestration frameworks, and cloud AI services.
- Guide engineering teams through implementation, deployment, scalability, and optimization of AI systems.
- Design secure, reliable, and production-ready AI workflows with monitoring, governance, and safety guardrails.
- Collaborate with clients, product teams, and delivery leaders to align AI solutions with business requirements.
- Optimize AI system performance, prompt engineering workflows, context management, and inference efficiency.
- Stay updated with emerging advancements in generative AI, autonomous agents, LLM ecosystems, and enterprise AI tooling.
Required Skills
Agentic AILLM OrchestrationLangChainLangGraphMulti-Agent SystemsPythonRAGPrompt EngineeringVector DatabasesAI ArchitectureLLMsAutonomous WorkflowsGenerative AIAI System Design
Preferred Skills
- Hands-on experience deploying production-grade agentic AI systems in enterprise environments.
- Strong understanding of prompt engineering, agent memory, tool usage, and AI safety guardrails.
- Experience with vector databases such as Pinecone, Weaviate, ChromaDB, or FAISS.
- Familiarity with cloud AI platforms including Azure OpenAI, AWS Bedrock, or Google Vertex AI.
- Experience with AI observability, evaluation frameworks, and scalable AI infrastructure.
- Strong leadership, stakeholder communication, and technical architecture skills.
- Education: Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field. Advanced AI/ML certifications or hands-on experience building enterprise AI systems are highly preferred.