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Job Description

The Senior Data Architect (AI Solutions) leads the design and implementation of cutting-edge AI platforms and data systems. This role combines strong hands-on engineering with strategic innovation to design, prototype, and deliver intelligent, data-driven solutions that power analytics, machine learning, and next-generation AI applications.

This role collaborates closely with business and technology teams to turn ideas into working solutions, enabling faster insights, better decisions, and enterprise-wide innovation through data.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

• 10+ years of experience in enterprise data architecture or engineering, with a strong hands-on focus on AI and cloud-native data platforms.

• Proven experience in designing, implementing, and optimizing large-scale AI systems, including LLM-based, GenAI, and agentic AI applications.

• Expertise in Python, SQL, and modern data frameworks (e.g., PySpark, Airflow, Snowflake, LangChain, Hugging Face, Vertex AI, OpenAI)

• Strong background in data modelling, distributed systems, and cloud architecture (AWS, GCP, or Azure).

• Experience developing and deploying AI/ML/GenAI pipelines leveraging vector databases and RAG frameworks.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field. • Experience with agentic AI design patterns, including tool-use orchestration, autonomous workflow agents, or AI copilots.

• Proficiency in API design, microservices, and containerization (Docker, Kubernetes).

• Demonstrated ability to rapidly prototype new AI concepts and transition successful PoCs into production-grade systems.