Solution Architect, Data Science and AI

Company Description

Hitachi Solutions is a global Microsoft solutions integrator passionate about developing and delivering industry-focused solutions that support our clients to deliver on their business transformation goals. Our industry focus, expertise, and intellectual property is what truly sets us apart. We have earned, and continue to maintain, a strategic relationship with Microsoft. Recognized for our achievements - teaming with our clients to deliver innovative digital solutions and services - is how we have achieved year after year recognition.

As their trusted advisor, we support our clients to deliver on their strategic business initiatives as they unify, automate, and modernize their data and operations to increase efficiency, reduce costs, and enhance their customer’s experience. Our over 3,000 team members across 14 countries, and our 18 years of 100% focus on Microsoft technologies and business applications, is how we deliver excellence through expert services and industry-focused cloud solutions.

A part of Hitachi, Ltd., our company has a long and rich history of innovation, financial strength, and international presence of one of the world’s largest companies. Since 1910, Hitachi, Ltd. has been a leader in manufacturing innovative products and solutions that support industry and social infrastructure around the globe supported by 303,000 employees in over 100 countries and across 864 companies.

Hitachi Solutions is a global Microsoft solutions integrator passionate about developing and delivering industry-focused solutions that support our clients to deliver on their business transformation goals. Our leadership in Global Dynamics 365 Field Service and Manufacturing is what truly sets us apart and enables us to maintain a strategic relationship with Microsoft.
 

Job Description

About the Role

The Solution Architect — Data Science & AI is a senior, client-facing technical leader responsible for designing and governing machine learning, advanced analytics, and generative AI solutions on Microsoft Azure and Databricks. This role demands deep expertise in data science, ML engineering, MLOps, and Gen AI — with enough architectural breadth across infrastructure, networking, and application development to participate credibly in cross-domain solution conversations. The ideal candidate is equally comfortable whiteboarding a model serving architecture during a presales pursuit as they are reviewing PySpark code, evaluating RAG retrieval quality, or designing an MLflow experiment tracking strategy.

This role spans the full engagement lifecycle, from presales architecture and deal shaping through delivery design assurance, ensuring that data science and AI solution intent is preserved from pursuit through implementation. The Solution Architect serves as a trusted technical authority to clients and internal teams alike, operating independently to lead workshops, shape solutions, and contribute to data strategy engagements alongside practice leadership.

Key Responsibilities

• Architect end-to-end machine learning and data science solutions on Azure and Databricks, from feature engineering through model serving and monitoring.

• Design and govern MLOps pipelines using Databricks MLflow, Model Serving, and related tooling to enable repeatable, production-grade model deployment.

• Architect generative AI solutions including Retrieval-Augmented Generation, agentic workflows, fine-tuning, document intelligence, embeddings, evaluation frameworks, and computer vision.

• Contribute to modern data estate architectures using Microsoft Fabric and/or Azure Databricks, including lakehouse patterns and medallion architecture, to support ML and analytics workloads.

• Contribute to client data strategy engagements including maturity assessments, analytics roadmaps, and governance frameworks in partnership with practice leadership.

• Independently lead client-facing presales engagements, discovery workshops, and architecture reviews as the primary technical authority on data science and AI pursuits.

• Develop level-of-effort estimates, architecture deliverables, and technical contributions to Statements of Work for client pursuits.

• Provide delivery design assurance and architectural governance across active data science and AI engagements, including code reviews of Python, PySpark, and ML model implementations.

• Design cloud-native Azure architectures using CAF and Well-Architected Framework principles as they apply to AI and data workloads.

Required Qualifications

• 8+ years in data science, ML engineering, or AI

***Travel up to 50%***

Qualifications

Required Qualifications

• 8+ years in data science, ML engineering, or AI-focused solution architecture roles.