AI Platform Architect
Apolis
Position Title: AI Platform Architect
Location Dallas, TX (Onsite)
Duration: Long Term Contract
Job Description:
Client is seeking an experienced AI Platform Architect to design and lead next-generation AI systems built on LLMs and agentic frameworks. This role focuses on architecting scalable, production-grade AI platforms across cloud environments, with a strong emphasis on RAG, agent orchestration, agent harness/skill building, observability, and gateway patterns. Immediate availability is required, and a background check is mandatory.
Basic Qualifications:
Required Skills:
Role and Responsibilities:
Location Dallas, TX (Onsite)
Duration: Long Term Contract
Job Description:
Client is seeking an experienced AI Platform Architect to design and lead next-generation AI systems built on LLMs and agentic frameworks. This role focuses on architecting scalable, production-grade AI platforms across cloud environments, with a strong emphasis on RAG, agent orchestration, agent harness/skill building, observability, and gateway patterns. Immediate availability is required, and a background check is mandatory.
Basic Qualifications:
- 8 years in software architecture with a strong focus on distributed systems
- Proven experience with LLMs, RAG architectures, and agentic systems (including agent harness and skill building)
- Strong hands-on expertise with Kubernetes and cloud-native/serverless architectures
- Proficiency in Python, JavaScript
- Strong communication and architecture storytelling skills
Required Skills:
- Experience with multi-agent frameworks (for example LangGraph, ADK) and emerging agent ecosystems
- Familiarity with LLMOps, evaluation frameworks, and AI governance
- Experience in GCP services such as BigQuery, Composer, Dataflow, Dataproc, Cloud function, Pub/Sub, and Cloud Storage
- Experience in implementation of security, governance, and compliance standards across GCP environments
- Experience with enterprise-scale AI platform deployments
Role and Responsibilities:
- Design end-to-end architectures for AI platforms leveraging RAG, agentic systems, and LLM-based applications
- Define and implement agentic patterns, including streaming, async workflows, multi-agent orchestration, and agent harness & skill development
- Architect platform components such as AI/LLM Gateways, agent frameworks, identity layers, and skill orchestration
- Build scalable solutions on Kubernetes and serverless cloud services
- Lead architecture across Amazon Web Services and/or Google Cloud Platform (GCP)
- Drive best practices for reliability, scalability, and performance of AI systems
- Translate complex AI capabilities into clear architectural narratives and business solutions
Vacancy posted 5 days ago
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