Job description

Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and help make a significant impact on our clients’ success. You’ll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation. Work you'll do As a Senior Snowflake FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include: Client Engagement • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions. • Partner with leaders, product owners, architects, and engineers to align priorities and delivery. • Lead working sessions to shape solutions and drive client outcomes. • Prototype and deliver working AI solutions using industry expertise and emerging capabilities. • Contribute independently within an FDE pod while mentoring newer team members. • Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success. • Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer. • Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital. Solution Engineering • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms. • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls. • Apply architecture decisions that balance quality, safety, latency, cost, and model risk. • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation. • Design extensible functionality, support sprint sizing, and align solutions with senior team members. • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations. The team Deloitte’s Government & Public Services (GPS) practice – our people, ideas, technology and outcomes – is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise. Our AI & Data offering provides a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offerings help clients innovate, enhance, and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively with organizational intelligence programs and differentiated strategies to win in their chosen markets. Qualifications Required: • 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 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. Preferred: • Current SnowPro Core 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. The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. ai&e fy27 profile

Requirements

Must-haves

Work you'll do
Client Engagement
Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
Lead working sessions to shape solutions and drive client outcomes.
Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
Contribute independently within an FDE pod while mentoring newer team members.
Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success.
Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.
Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital.
Solution Engineering
Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.

Nice-to-haves

Current SnowPro Core 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.
ai&e fy27 profile

Application prep

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aici/cdllmawsazureml

Platform: avature
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