Note: The job is a remote job and is open to candidates in USA. ITMC Systems, Inc is seeking a highly experienced Generative AI Solutions Architect to lead the design, architecture, and implementation of enterprise-scale AI solutions within an AWS-based enterprise AI platform. The role will evaluate GenAI use cases, design scalable and secure architectures, guide agentic AI and RAG implementations, establish governance and guardrails, and support production deployment across AWS and Kubernetes environments.
Responsibilities
- Architect and design scalable Generative AI solutions that support enterprise-wide business initiatives
- Evaluate incoming AI use cases and define optimal architecture patterns, platform integrations, and implementation strategies
- Lead the design and deployment of agentic AI applications using frameworks such as LangChain, LangGraph, and modern orchestration technologies
- Design and implement Model Context Protocol (MCP) architectures to enable secure and dynamic integration between agents, tools, APIs, and enterprise data sources
- Define end-to-end solution architecture for GenAI applications involving text, document, image, and tabular data processing
- Build enterprise-grade Retrieval Augmented Generation (RAG) architectures utilizing vector databases, embeddings, retrieval optimization, and prompt orchestration
- Establish standards and governance around model selection, prompt engineering, evaluation frameworks, hallucination reduction, bias mitigation, and AI safety
- Implement guardrails for security, compliance, PII protection, authorization, and responsible AI practices
- Design scalable multi-agent architectures and determine when to leverage single-model versus multi-model approaches
- Drive architecture decisions around caching strategies, retrieval optimization, chunking methodologies, embedding strategies, and inference performance
- Partner with engineering, data science, MLOps, and business teams to ensure successful deployment and adoption of GenAI solutions
- Support deployment and operationalization of AI workloads within AWS and Kubernetes-based environments
- Mentor engineering teams on GenAI architecture best practices and emerging AI technologies
Skills
- 8-10+ years of experience in Software Engineering, Data Engineering, Machine Learning, or Artificial Intelligence
- Proven experience architecting and delivering enterprise-scale AI, ML, or Generative AI platforms
- Deep expertise with Large Language Models (LLMs) and Generative AI applications
- Hands-on experience designing and deploying agentic AI systems and multi-agent architectures
- Strong experience implementing Model Context Protocol (MCP) architectures and agent orchestration frameworks
- Extensive experience with Retrieval Augmented Generation (RAG) solutions and vector search architectures
- Strong Python development skills
- Experience delivering machine learning solutions involving:
- Time Series Analysis
- Sentiment Analysis
- Topic Modeling
- Predictive Analytics
- Strong experience with AWS cloud services and enterprise cloud deployments
- Experience with:
- PySpark
- Apache Spark
- FastAPI
- Kubernetes
- Docker
- Enterprise API development
- Experience supporting production AI systems with monitoring, observability, governance, and lifecycle management
- Strong understanding of prompt engineering, model evaluation, fine-tuning, and inference optimization
- AWS Certification strongly preferred
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