AI Architect

Technologent•Sunrise, FL

1d•Onsite

About The Position

We are seeking an AI Architect to join the enterprise platform engineering team supporting a large-scale internal developer ecosystem for a customer. This role focuses on building intelligent, agent-driven capabilities across developer platforms that improve engineering productivity, software delivery, and enterprise API usage. The ideal candidate works on next-generation platform capabilities used across engineering teams of the customer, building AI-native features that enhance how developers design, build, and deploy software at scale.

Requirements

7+ years of Software Architect experience with strong expertise in JavaScript/TypeScript and React.
Hands-on experience building and deploying generative AI or LLM-based production systems.
Strong understanding of prompt engineering and LLM orchestration techniques.
Experience with agentic AI frameworks such as LangGraph or similar workflow-based systems.
Practical knowledge of RAG architectures and vector-based search systems.
Experience integrating APIs and building end-to-end AI-enabled applications.
Strong experience with CI/CD pipelines and DevOps practices.
Hands-on experience with containerization (e.g., Docker) and cloud-native deployments.
Strong system design and scalable software architecture skills.
Ability to troubleshoot distributed systems and optimize AI pipeline performance.
Strong collaboration and communication skills across engineering and platform teams.

Nice To Haves

Experience building AI copilots or internal developer productivity tools.
Familiarity with enterprise API platforms and developer ecosystems.
Exposure to AI observability, monitoring, and evaluation frameworks.
Understanding of distributed systems and cloud architecture.
Experience in large-scale enterprise engineering environments.
Knowledge of responsible AI practices and secure AI deployment.
Familiarity with embeddings, vector databases, and semantic search systems.

Responsibilities

Design and build AI-powered applications and agent-based systems within enterprise developer platforms for the Customer.
Develop generative AI solutions using LLMs, orchestration frameworks, and retrieval-augmented generation (RAG) architectures.
Build production-grade AI systems integrating machine learning models, APIs, and backend services into scalable applications.
Create AI-driven developer productivity tools such as coding assistants, workflow automation, and intelligent recommendations.
Ensure AI systems meet enterprise standards for reliability, scalability, observability, and compliance requirements of the Customer.
Implement agentic workflows using frameworks such as LangGraph and MCP-style integrations.
Design and optimize RAG pipelines for enterprise knowledge retrieval and contextual intelligence.
Integrate AI features into internal developer platforms, APIs, and tooling ecosystems of the Customer.
Build CI/CD pipelines for AI model deployment, versioning, and lifecycle management.
Deploy containerized AI services using modern cloud-native engineering practices.
Improve model performance through prompt engineering, evaluation frameworks, and iterative tuning.
Collaborate with cross-functional engineering teams within the Customer organization to deliver AI capabilities.
Document system architecture, AI workflows, and integration patterns for enterprise adoption.