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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Forward Deployed Engineer, Microsoft AI & Data - **Company:** Deloitte T.T.L. - **Location:** Las Vegas, NV, United States - **Experience:** Expert - **Salary:** $189,200.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Continuous Integration, Information Engineering, Data Infrastructure, Software Debugging, Monitoring of Systems, Identity and Access Management, IT Management, Software Engineering, Data Streaming, Management of Software Versions, Data Logging, Google Cloud, Enterprise Software Applications, Cloud Platform System, Feature Engineering, Large Language Models, Prompt Engineering, Apache Spark, Model Validation, HybridCloud, Event Driven Architecture, AI Platforms, Information Technology, Low Latency, Data Management, Machine Learning Operations, Data Pipelines, Microservices - **Published:** July 24, 2026 - **Apply:** https://dejobs.org/x/x/628CE3A986FA4637B3117875B2EA0B53/job/ ## About the Role * 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 of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments * 1+ years of experience with Microsoft AI&Data including hands on experience with Azure AI Foundry * 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve * Limited immigration sponsorship may be available, * Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking) * Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments * Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management * Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures * Experience operating within hybrid onshore/offshore teams * Familiarity with security, privacy, and compliance considerations ## Description As a Lead Microsoft AI&Data FDE, you will serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production for Deloitte's most strategic clients. You'll set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team. You'll translate engineering trade-offs into clear decisions for client leaders when needed. Your ability to influence decisions at the C-suite level, while maintaining hands-on technical credibility, is what sets you apart. Pods under your leadership may be deployed onshore with clients or in hybrid onshore/offshore configurations, leveraging Deloitte's global delivery capability to maximize speed and scale. Client Engagement * Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders * Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scaling * Navigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared vision * Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements-contributing to pipeline development and deal shaping. Cross-Functional Pod Leadership & Program Governance * Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health * Enforce delivery standards across the pod: sprint cadences, stakeholder communication plans, risk management, and quality gates * Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience. * Mentor and develop junior FDEs GenAI Solution Development * Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below) * 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-ensuring production-grade quality and scalability. * Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards. Engineering & Data Foundations * Review and contribute to production-quality code * Guide architecture of data pipelines powering GenAI use cases * Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices * Deep familiarity with cloud environments (AWS, Azure, and/or Google Cloud) The team AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements. ## Related Videos - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Unleash the power of 5G in your code: transform your apps](https://www.wearedevelopers.com/videos/1567-unleash-the-power-of-5g-in-your-code-transform-your-apps) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? 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