Forward Deployed Engineer- AWS

About the role

Forward Deployed Engineers (FDE) at Deloitte help clients transform AI ambition into enterprise-scale impact by pairing leading class engineering with pod-based delivery and vertical expertise.

Responsibilities

• 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.
• 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.

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.

Requirements

• Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering
• 3+ years of experience in software engineering, data engineering, data science, or analytics engineering
• 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products; Amazon Bedrock, Bedrock Agents, Knowledge Bases, Guardrails
• 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
• 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

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

Benefits

We offer a comprehensive benefits package including:

• Discretionary annual incentive program
• Flexible work arrangements
• Professional development opportunities
• Inclusive culture fostering diversity and inclusion
• Competitive compensation and benefits

Pay

The wage range for this role is $134,500 to $265,100, taking 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.

Schedule

Travel requirements may vary based on the work you do and the clients and industries/sectors you serve, typically averaging 50%.