Fullstack AI Architect

Kyndryl

Agentic AI Architect at Kyndryl designing and delivering distributed architectures for AI systems. Collaborating on large-scale, cloud-based enterprise solutions while integrating AI capabilities.

Posted 7/7/2026full-timeRemote • Texas • 🇺🇸 United StatesMid-LevelSenior💰 $138,480 - $263,160 per yearWebsite

Tech Stack

Tools & technologies

AngularAWSAzureCloudDockerFirebaseGoogle Cloud PlatformJavaScriptKafkaKubernetesMongoDBNode.jsNoSQLPostgresPythonRabbitMQReactRedisSQLTypeScriptVue.js

About the role

Key responsibilities & impact

Design and deliver distributed architectures for large-scale, cloud-based enterprise systems (AWS, Azure, GCP).
Integrate Agentic AI capabilities into enterprise software.
Act as a technical authority, setting standards for security, scalability, and performance, ensuring poor code or weak architecture is prevented from entering production.
Translate vague customer requirements into actionable technical designs.
Lead discussions, challenge ideas, and align teams on a clear technical direction.
Collaborate with engineers and stakeholders to ensure timely delivery of MVPs and production-ready solutions.
Design and develop robust back-end services using Node.js, Python, or other back-end technologies.
Integrate large language models (LLMs) and multimodal AI models into applications.
Optimize application performance, ensuring efficiency in AI inference and API response times.
Ensure security, scalability, and compliance of AI-driven applications.
Stay up to date with the latest advancements in Generative/Agentic AI, web development, and cloud technologies.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
6+ years of experience in full-stack development, with a track record of building scalable, production-ready systems.
Strong proficiency in JavaScript/TypeScript, Python, and modern front-end frameworks (React, Vue, or Angular).
Experience with agentic frameworks such as LangChain, AutoGen or CrewAI.
Hands-on experience with integrating AI models via APIs (OpenAI, Hugging Face, etc.).
Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG) techniques.
Experience with cloud platforms (e.g., AWS, Azure, GCP), containerization (Docker, Kubernetes), and CI/CD pipelines.
Strong understanding of database technologies (SQL, NoSQL, Firebase, MongoDB, PostgreSQL).
Ability to design scalable and maintainable architectures for AI-driven applications.
Capable of working closely with cross-functional teams to deliver cohesive, end-to-end functionality.
Knowledge of message queues (e.g., RabbitMQ, Kafka) and caching systems (e.g., Redis).

Benefits

Comp & perks

medical and dental coverage
disability
retirement benefits
paid leave
paid time off
discretionary annual bonus program
professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Node.jsPythonReactVueAngularLangChainAutoGenOpenAI API IntegrationSQLNoSQL

Soft Skills

Technical LeadershipCollaborationProblem-Solving

Certifications

Bachelor’s Degree in Computer ScienceSoftware Engineering