AI Solutions Architect

HeartCentrix Solutions; Dallas (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

HeartCentrix Solutions seeks an experienced AI Solutions Architect to lead the design of an enterprise AI platform, focusing on agentic AI, LLM integrations, and AI services.

You will mentor engineering teams, define scalable, production-ready architectures, and set technical standards across the organization.

Strong hands-on experience with distributed systems, cloud platforms, and modern AI tooling will help you drive major architectural decisions and platform reliability.

Qualifications

• 10+ years of software architecture and engineering experience.
• 3+ years designing AI/ML platforms or GenAI applications.
• Strong experience with Python and Java, Go, or TypeScript; familiarity with LLMs and agentic AI.

Responsibilities

• Design architectures for agentic AI platforms, LLM orchestration, and AI services.
• Define API, microservices, and event-driven architecture standards.
• Lead architecture reviews, technical decisions, and engineering best practices.
• Collaborate with software and ML engineers to build scalable, secure AI solutions.
• Evaluate emerging AI frameworks and improve platform reliability, observability, and performance.

Skills

AI architecture

Distributed systems

REST APIs / gRPC

Cloud platforms

Python

Java/Go/TypeScript

LLMs & Agentic AI

Tools

LangChain

LangGraph

Semantic Kernel

CrewAI

AutoGen

AWS

Azure

GCP

Job description

We're looking for an experienced AI Solutions Architect to lead the design and architecture of an enterprise AI platform. You'll define scalable, production-ready solutions for agentic AI systems, LLM integrations, and AI services while mentoring engineering teams and driving technical standards.

What You'll Do

• Design and evolve architectures for agentic AI platforms, LLM orchestration, and AI services.
• Define API, microservices, and event-driven architecture standards.
• Lead architecture reviews, technical decisions, and engineering best practices.
• Collaborate with software and ML engineers to build scalable, secure AI solutions.
• Evaluate emerging AI frameworks and improve platform reliability, observability, and performance.

What You'll Need

• 10+ years of software architecture and engineering experience.
• 3+ years designing AI/ML platforms or GenAI applications.
• Strong experience with Python and Java, Go, or TypeScript.
• Experience with LLMs, Agentic AI, RAG, prompt engineering, and orchestration frameworks (LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen).
• Expertise in distributed systems, microservices, REST/gRPC APIs, and cloud platforms (AWS, Azure, or GCP).

Nice to Have

• Vector databases (Pinecone, Weaviate, pgvector).
• Knowledge graphs.
• TOGAF or other architecture certifications.

Key Skills: AI Architecture, Agentic AI, LLMs, RAG, LangChain, LangGraph, Semantic Kernel, Python, Microservices, Distributed Systems, Cloud Architecture, MLOps.