Lead Snowflake Forward Deployed Engineer - GPS
- 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.
- 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
- 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.
- 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)
- Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
- 10+ 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 Snowflake including hands on experience with one of the following key platform technologies; Cortex AI, Cortex LLM Functions, Cortex Agents, Arctic Embed
- 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
- Current SnowPro Core Certification
- Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
- Ability to obtain and maintain a US government security clearance
- Current SnowPro Advanced: Architect, Data Engineer, Data Scientist
- 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
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