Lead Forward Deployed Engineer, Microsoft AI & Data Engineering and Product | Engineering and Product Generalist

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Company Overview
A leading global professional services organization is seeking a senior Forward Deployed Engineer to help clients implement AI and GenAI solutions at enterprise scale. The organization specializes in technology consulting, AI, data engineering, and digital transformation, delivering high-impact solutions across industries and enabling clients to modernize operations while driving innovation.

Position Summary
The Lead Forward Deployed Engineer (FDE) serves as a senior practitioner embedded with strategic clients, leading engineering pods to design, build, and deploy AI and GenAI solutions. This role combines technical leadership, client engagement, and hands-on engineering to ensure production-grade results and measurable business impact.

Responsibilities

Client Engagement

• Serve as the senior client-facing engineering partner, building trusted advisor relationships with product, data, and platform leaders
• Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk), and create phased plans from prototype to production
• Navigate organizational complexity to align executive sponsors, IT leadership, and business owners on shared AI initiatives
• Represent FDE capabilities in client pursuits, executive briefings, and platform partner engagements

Cross-Functional Pod Leadership & Program Governance

• Lead FDE pods of 2–5 engineers, managing execution, resources, escalations, and delivery health
• Enforce delivery standards across sprints, stakeholder communication, risk management, and quality gates
• Coordinate multi-pod or multi-workstream engagements to ensure consistent architecture and client experience
• Mentor and develop junior FDEs

GenAI Solution Development

• Architect and oversee LLM-enabled applications including copilots, assistants, agentic workflows, and knowledge search experiences
• Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls
• Govern end-to-end RAG pipeline design including ingestion, chunking, embedding, vector retrieval, and hybrid search
• Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance

Engineering & Data Foundations

• Review and contribute to production-quality code
• Guide architecture of data pipelines powering GenAI solutions
• Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices
• Maintain deep familiarity with cloud environments such as AWS, Azure, and Google Cloud

Required Qualifications

• Bachelor’s degree (or equivalent) in Computer Science, Data Science, or Engineering
• 7+ years of experience in software engineering, data engineering, data science, or analytics engineering
• 1+ years hands-on experience building and deploying GenAI/LLM solutions in production or client environments
• 1+ years experience with Microsoft AI & Data, including Azure AI Foundry
• 1+ years leading project workstreams and translating business problems into AI solutions
• Experience building reliable, maintainable, and well-documented code
• Ability to travel up to 50% depending on client and project needs

Preferred Qualifications

• Experience with cloud environments (AWS, Azure, Google Cloud) and common services (storage, compute, IAM, networking)
• Experience working directly with client technical teams in fast-paced, ambiguous delivery environments
• Data engineering experience with Spark, Airflow/dbt, streaming, data modeling, or ML feature engineering and evaluation
• Experience with MLOps/LLMOps practices including evaluation frameworks, model monitoring, and prompt management
• Integration of LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures
• Experience operating in hybrid onshore/offshore teams
• Familiarity with security, privacy, and compliance considerations

Disclaimer
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