Solution Architect – Microsoft

Job Overview

Microsoft is seeking an experienced Solution Architect with a strong background in software engineering, enterprise data platforms, AI, and delivery leadership. This role combines architecture expertise with hands-on technical leadership, client engagement, solutioning, and delivery ownership. The successful candidate will help customers modernize complex data environments, adopt AI-first engineering practices, and build scalable solutions that deliver measurable business outcomes.

The position is suited to a senior technology professional with 12 or more years of software or solution engineering experience, including significant experience in architecture and delivery leadership. You will work across enterprise data architecture, large-scale data processing, database performance, AI and machine learning enablement, solution design, pre-sales, and production delivery.

A major focus of the role is helping organizations move toward modern, AI-enabled data platforms. This includes designing target-state architectures, leading modernization programs, improving data engineering practices, integrating AI workloads, and establishing reliable operational models. The role also requires the ability to engage confidently with clients, senior stakeholders, engineering teams, and delivery leaders.

Key Responsibilities

• Lead complex technology engagements from strategy and architecture through implementation, production rollout, and continuous improvement.
• Translate customer business objectives into scalable technical architectures, delivery plans, milestones, and risk mitigation strategies.
• Embed AI-first practices into engineering and delivery workflows through automation, intelligent orchestration, and reusable technical assets.
• Provide architecture and technical leadership across enterprise data modernization programs.
• Design target-state data platforms while balancing scalability, resilience, performance, security, governance, and total cost of ownership.
• Lead large-scale batch and streaming data engineering initiatives and establish engineering standards, SLAs, SLOs, and performance baselines.
• Guide database performance assessments, workload sizing, capacity planning, query optimization, indexing strategies, and storage improvements.
• Design AI-enabled data engineering workflows for data discovery, preparation, profiling, validation, metadata enrichment, documentation, and optimization.
• Architect AI and machine learning solutions using cloud AI platforms, AI agents, retrieval-augmented generation pipelines, and inference workloads.
• Establish monitoring, observability, drift detection, performance measurement, and cost optimization practices for production AI systems.
• Promote responsible AI, governance, explainability, privacy, and human oversight in enterprise AI solutions.
• Support pre-sales activities through technical solutioning, estimates, demonstrations, proposals, and architecture guidance.
• Step into at-risk projects, assess delivery challenges quickly, and establish practical recovery strategies.
• Lead cross-functional engineering and consulting teams while mentoring engineers and encouraging technical excellence.
• Drive adoption of Agile, DevOps, CI/CD, test-driven development, observability, secure coding, and modern engineering practices.
• Build reusable accelerators, reference architectures, prototypes, and production-ready assets that can improve delivery efficiency across engagements.

Required Skills

Candidates should have extensive experience in software or solution engineering and a strong track record of architecture and delivery leadership. The role requires the ability to move between strategic architecture discussions and hands-on technical problem solving.

Strong expertise in enterprise data architecture, data engineering, distributed processing, database platforms, cloud technologies, and AI-enabled systems is required. Experience leading modernization initiatives across complex enterprise environments is particularly relevant.

Candidates should understand large-scale data pipelines, both batch and streaming, and be comfortable with performance engineering, capacity planning, monitoring, and operational support. Strong knowledge of architecture principles, engineering standards, security, governance, and production reliability is also important.

Client-facing communication is a major part of the role. Candidates should be able to explain complex technical decisions to senior business and technology stakeholders and connect architecture choices to measurable business outcomes.

Preferred Skills

Experience with Microsoft's data and AI ecosystem is highly relevant, including Microsoft Purview, Azure Synapse Analytics, Azure Data Factory, Azure Machine Learning, Azure OpenAI, and Azure AI Services.

Experience with partner and third-party data platforms such as Snowflake and Teradata is also valuable. Candidates with expertise in Apache Spark, Databricks, Kafka, Hadoop, Hive, HDInsight, and large-scale distributed data processing will be well aligned with the role.

Database expertise across Azure SQL, SQL Server, PostgreSQL, MySQL, MariaDB, Oracle, Teradata, Netezza, Cosmos DB, and columnar analytics platforms is relevant. Experience with query tuning, execution plan analysis, indexing, wait-state analysis, storage optimization, and workload sizing is particularly useful.

Education

A Bachelor's degree in Computer Science, Engineering, or a related field is required, or equivalent practical experience. Relevant professional certifications are considered a plus.

Experience

The role requires 12 or more years of experience in software or solution engineering, with at least 10 years in architecture and delivery leadership positions. Candidates should demonstrate experience leading complex, multidisciplinary projects and working with enterprise customers.

Relevant experience includes enterprise architecture, data modernization, large-scale data engineering, database performance, AI and machine learning delivery, solution consulting, pre-sales, production support, and technical leadership.

Required Technologies

The technical environment covers Microsoft and partner data platforms, distributed processing, databases, cloud AI services, and modern engineering practices. Key technologies and platforms include:

• Microsoft Purview
• Azure Synapse Analytics
• Azure Data Factory
• Snowflake
• Teradata
• Apache Spark
• Databricks
• Kafka
• Hadoop
• Hive
• HDInsight
• Azure SQL
• SQL Server
• PostgreSQL
• MySQL
• MariaDB
• Oracle
• Netezza
• Cosmos DB
• Azure Machine Learning
• Azure OpenAI
• Azure AI Services
• Large Language Models
• AI Agents
• RAG Pipelines
• AIOps
• DataOps
• Agile
• DevOps
• CI/CD
• Observability

Soft Skills

Strong stakeholder management and executive communication are essential. The successful candidate should be comfortable advising senior leaders, working directly with customers, resolving ambiguity, and making decisions in high-pressure consulting environments.

A consultative mindset, structured problem-solving ability, technical curiosity, and strong ownership are important. Candidates should also be capable of mentoring teams, influencing technical direction, managing competing priorities, and communicating trade-offs clearly.

Benefits of Working in this Role

This role offers the opportunity to work on complex enterprise technology programs involving cloud data platforms, artificial intelligence, large-scale data engineering, and modern solution architecture. It provides exposure to customer transformation initiatives and opportunities to influence architecture, delivery strategy, reusable engineering assets, and AI adoption.

The position can also help experienced technology leaders deepen their expertise across enterprise data modernization, AI engineering, cloud architecture, database performance, and consulting-led delivery.

Work Mode

The job posting specifies a hybrid work arrangement requiring 3 days per week in the office. Travel is expected to be less than 25%.

Location

The supplied job description does not specify a city or state in the available posting content. Applicants should verify the current Microsoft job listing for the exact work location before applying.

Who Should Apply

This opportunity is designed for senior solution architects, enterprise architects, data architects, AI architects, technical delivery leaders, and experienced consulting professionals with 12 or more years of relevant engineering experience.

It is particularly suitable for professionals who have led enterprise data modernization programs, designed large-scale data platforms, implemented AI and ML solutions, supported production systems, or advised customers on cloud and data strategy.

Candidates with strong Microsoft Azure expertise, distributed data engineering experience, database performance skills, AI architecture knowledge, and client-facing consulting experience should consider applying.

Career Growth

The role provides broad exposure across enterprise architecture, cloud data engineering, artificial intelligence, solution consulting, technical delivery, and executive stakeholder management. Professionals can strengthen their ability to lead large transformation programs while developing deeper expertise in AI-first engineering, modern data platforms, responsible AI, and enterprise architecture.

Application Advice

When applying for this Solution Architect opportunity, highlight the scale and outcomes of the programs you have led. Clearly describe architecture responsibilities, delivery ownership, customer engagement, team leadership, and measurable improvements in performance, reliability, cost, or business value.