AI Solution Architect

Robotic Technologies Automation; Tampa (FL); Remote; USD 140,000 - 190,000; Full time

Job summary

Robotic Technologies Automation in Tampa, FL seeks an experienced AI Solution Architect to design and implement scalable AI systems. You will lead end-to-end AI/ML solutions, align with business goals, and drive enterprise integration across systems and APIs.

Responsibilities include building architectures with LLMs, RAG, AI agents, and vector databases; deploying via MLOps, ensuring security and governance; collaborating with data scientists and engineers.

Qualifications

• 10+ years in software or enterprise architecture.
• Experience with AI/ML architecture and Generative AI.
• Hands-on with Azure OpenAI / AWS Bedrock / Vertex AI / OpenAI.
• Strong Python programming.
• Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel.
• Knowledge of vector DBs like Pinecone, FAISS, Weaviate.
• Design REST APIs and microservices.
• Cloud platforms knowledge (Azure/AWS/GCP).
• MLOps/LLMOps, model monitoring and deployment pipelines.
• Responsible AI, data privacy, and governance.

Responsibilities

• Design and architect end-to-end AI/ML and Generative AI solutions for enterprise applications.
• Develop scalable AI architectures leveraging LLMs, RAG, AI Agents, and vector databases.
• Define solution architecture, technical roadmaps, design patterns, and architecture standards.
• Evaluate and implement AI platforms such as Azure OpenAI, AWS Bedrock, Vertex AI, and OpenAI.
• Design and implement RAG pipelines, prompt engineering, embeddings, semantic search, and vector indexing.
• Build and integrate AI-powered applications using Python, REST APIs, and microservices.
• Work with LangChain, LangGraph, LlamaIndex, Semantic Kernel, and Hugging Face.
• Design AI agent workflows, tool calling, multi-agent orchestration, and MCP-based integrations.
• Integrate AI solutions with enterprise systems, databases, APIs, and cloud platforms.
• Ensure AI solutions meet security, scalability, governance and compliance requirements.
• Establish MLOps and LLMOps practices for deployment, monitoring, and evaluation.
• Collaborate with business stakeholders, data scientists, ML engineers, and development teams.

Skills

AI/ML architecture

Generative AI

Python

REST APIs

MLOps/LLMOps

Cloud platforms (Azure/AWS/GCP)

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Pinecone

Weaviate

Docker

Kubernetes

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: AI Solution Architect
Location: Tampa, FL(Remote)
Duration: 24 Months + Extension
Bill Rate: $86/hour (C2C)
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description:

We are seeking an experienced AI Solution Architect to design, develop, and implement scalable, secure, and enterprise-grade AI solutions. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), cloud architecture, machine learning, and enterprise application integration. The candidate will be responsible for defining AI architecture, leading technical implementation, and aligning AI solutions with business objectives.

Key Responsibilities:

• Design and architect end-to-end AI/ML and Generative AI solutions for enterprise applications.
• Develop scalable AI architectures leveraging LLMs, RAG (Retrieval-Augmented Generation), AI Agents, and vector databases.
• Define solution architecture, technical roadmaps, design patterns, and architecture standards.
• Evaluate and implement AI platforms such as Azure OpenAI, AWS Bedrock, Google Vertex AI, and OpenAI.
• Design and implement RAG pipelines, prompt engineering, embeddings, semantic search, and vector indexing.
• Build and integrate AI-powered applications using Python, REST APIs, and microservices.
• Work with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, and Hugging Face.
• Design AI agent workflows, tool calling, multi-agent orchestration, and MCP-based integrations.
• Integrate AI solutions with enterprise systems, databases, APIs, and cloud platforms.
• Ensure AI solutions meet enterprise security, scalability, performance, governance, and compliance requirements.
• Establish MLOps and LLMOps practices for model deployment, monitoring, evaluation, and continuous improvement.
• Collaborate with business stakeholders, data scientists, ML engineers, and development teams.

Required Technical Skills:

• 10+ years of experience in software engineering, solution architecture, or enterprise architecture, with relevant AI/ML experience.
• Strong experience in AI/ML architecture and Generative AI implementations.
• Expertise in Large Language Models (LLMs), RAG, prompt engineering, and AI Agents.
• Hands-on experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or OpenAI.
• Strong programming experience in Python.
• Experience with LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
• Knowledge of vector databases such as Pinecone, FAISS, ChromaDB, Weaviate, or Azure AI Search.
• Experience designing REST APIs, microservices, and enterprise integrations.
• Strong knowledge of cloud platforms (Azure/AWS/GCP).
• Experience with Docker, Kubernetes, CI/CD, and cloud-native architecture.
• Knowledge of MLOps/LLMOps, model monitoring, AI evaluation, and deployment pipelines.
• Understanding of AI security, Responsible AI, data privacy, and governance.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.