Senior Forward Deployed Engineer, Microsoft AI&Data

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Company Overview

A global professional services organization is expanding its AI & Engineering team to help enterprises accelerate AI adoption and digital transformation. The team specializes in designing, building, and deploying AI-powered solutions that integrate software engineering, cloud technologies, data platforms, and Generative AI. By combining technical excellence with industry expertise, the organization delivers scalable, enterprise-grade solutions that help clients modernize operations and drive measurable business outcomes.

The organization is seeking a Senior Forward Deployed Engineer, Microsoft AI&Data to partner directly with enterprise clients in designing, developing, and deploying AI-powered solutions. This role combines software engineering, AI expertise, and client engagement to rapidly prototype and deliver production-ready Generative AI applications that create measurable business value.

Key Responsibilities

• Partner directly with enterprise clients to identify business challenges and translate high-value Generative AI use cases into practical solutions.
• Collaborate with business leaders, product owners, architects, and engineering teams to align technical delivery with business objectives.
• Lead client workshops and solution design sessions to define AI strategies and implementation plans.
• Prototype, develop, and deploy production-ready AI solutions using Microsoft AI and Azure technologies.
• Contribute independently within engineering delivery teams while mentoring junior engineers.
• Coach client teams and end users on AI platform capabilities, adoption strategies, and best practices.
• Support business development by creating demonstrations, proof-of-concepts, technical proposals, and solution documentation.
• Conduct design reviews, code reviews, and technical mentoring to strengthen engineering quality.
• Build AI-enabled applications, agentic workflows, and enterprise AI platforms.
• Develop scalable AI engineering patterns, automation frameworks, and human-in-the-loop workflows.
• Apply architectural best practices to balance performance, scalability, security, cost, and AI model governance.
• Deliver production-quality software using modern engineering practices including testing, CI/CD, logging, version control, and documentation.
• Design reusable software components, prompt libraries, runbooks, and reference implementations.
• Support sprint planning, solution estimation, and technical delivery alongside senior engineering leaders.

Required Qualifications

• Bachelor’s degree (or equivalent) in Computer Science, Data Science, Engineering, or a related field.
• 5+ years of experience in software engineering, data engineering, data science, or analytics engineering.
• 1+ years of hands-on experience building and deploying Generative AI or Large Language Model (LLM) solutions in production or client environments.
• 1+ years of hands-on experience with Microsoft AI & Data technologies, including Azure AI Foundry.
• Experience leading project workstreams and translating business requirements into AI-driven solutions.
• Experience developing reliable, maintainable, and well-documented software applications.
• Ability to travel approximately 50% based on client and project requirements.
• Strong communication and stakeholder management skills.

Preferred Qualifications

• Experience working with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
• Experience collaborating directly with enterprise technical teams in fast-paced delivery environments.
• Knowledge of data engineering technologies including Spark, Airflow, dbt, streaming platforms, or data modeling.
• Experience with MLOps or LLMOps practices including evaluation frameworks, prompt management, and model monitoring.
• Experience integrating AI solutions with enterprise systems through APIs, microservices, or event-driven architectures.
• Experience working within hybrid onshore and offshore engineering teams.
• Familiarity with enterprise security, privacy, governance, and compliance best practices for AI solutions.

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