Job description

At Deloitte, Forward Deployed Engineers (FDE) don’t just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations. Recruiting for this role ends on 10/30/2026. Work you’ll do As a Senior Microsoft AI&Data 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 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. Required qualifications • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering. • 5+ 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 Preferred qualifications • 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.

Requirements

Must-haves

Recruiting for this role ends on 10/30/2026.
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.
Design extensible functionality, support sprint sizing, and align solutions with senior team members.

Nice-to-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aici/cdllmazureawsml

Platform: avature
Effort: medium