AI Application Architect

Introduction

A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio

Your role and responsibilities

As an Architect in IBM Consulting, you'll serve as a leader in defining solutions for clients. You'll be the advocate for the client while guiding the technical team to implementation.

You'll collaborate with client stakeholders and internal partners to understand the business problem and requirements, constraints of the system and concerns of the various stakeholders to systematically transform detailed solutions (architectures) for the client.

Your primary responsibilities include:

• Innovative Systems Design for Optimal Performance:
  Design centralized or distributed systems that both address the user's requirements and perform efficiently and effectively.
• End-to-End Data Architecture Leadership:
  Manage end-to-end data architecture, starting from selecting the platform, designing a technical architecture and developing the application.
• Data Analysis and Insightful Reporting:
  Interpret data, analyze results using statistical techniques and provide ongoing reports discovering key insights.

Required technical and professional expertise

• 7-12+ years total experience in software engineering, data engineering, machine learning, or cloud architecture.
• Deep experience in at least one cloud platform.
• Architecture & System Design Experience; high-level solution architecture diagrams.

Hands-on experience is expected in:

• Building and deploying ML models (supervised, unsupervised, deep learning).
• Model lifecycle & MLOps: MLflow, Kubeflow, Vertex AI, Sage Maker.
• Feature engineering and dataset management.

Large Language Models & Generative AI Experience

• Experience with LLM fine-tuning, RAG pipelines, vector databases.
• Familiarity with OpenAI, Anthropic, Llama, Hugging Face.
• Prompt engineering, model evaluation, guardrails & safety.

Preferred technical and professional experience Experience in Data Engineering & Data Architecture

• Data pipelines:
  Spark, Airflow, Kafka.
• Data lakes & warehouses:
  Snowflake, Big Query, Redshift.
• ETL/ELT design.
• Data governance & quality frameworks.

Security, Governance, and Responsible AI Experience

• AI governance frameworks.
• Privacy‑by‑design.
• Model risk management.

IBM is committed to creating a diverse environment and is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

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