D

Deloitte

Audits companies and advises on tax and technology

Senior AWS Forward Deployed Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeAtlanta, GA, USA

About the Job

Requirements

  • A bachelor's degree or equivalent in Computer Science, Data Science, or Engineering.
  • At least 7 years of experience in software engineering, data engineering, data science, or analytics engineering.
  • At least 1 year of hands-on experience building and deploying generative AI or large language model-powered solutions in client or production environments.
  • At least 1 year of experience with AWS, including hands-on experience with Amazon Bedrock, Bedrock Agents, Knowledge Bases, or Guardrails.
  • At least 1 year of experience leading project workstreams or engagements and translating business problems into AI solutions.
  • At least 1 year of experience building reliable, maintainable, and well-documented code.
  • At least one of the listed AWS Associate certifications: Solutions Architect, Developer, SysOps Administrator, Data Engineer, or Machine Learning Engineer.
  • Ability to travel 50% on average, based on assigned work and clients or industries served.
  • Must be legally authorized to work in the United States without employer sponsorship, now or in the future.
  • Ability to obtain and maintain a U.S. government security clearance.
  • Ability to work independently and collaboratively as part of a team.
  • Effective written and verbal communication skills.
  • Meticulous attention to detail and quality of work product.
  • Ability to build and sustain professional relationships.
  • Ability to lead projects or workstreams.
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment.
  • Strong interpersonal skills and professional demeanor.
  • Ability to meet deadlines.
  • Ability to mentor and provide clear guidance to others.

Responsibilities

  • Embed with clients to identify business needs and translate high-value generative AI 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 a forward deployed engineering pod while mentoring newer team members.
  • Coach client teams and end users on platform capabilities and AI enablement, build trusted relationships, manage expectations, and support long-term engagement success.
  • Support sales and delivery end to end by developing demos and proofs of concept, contributing to proposals and oral presentations, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.
  • Mentor other forward deployed engineers through design and code reviews and feedback, and contribute reusable components to intellectual capital.
  • 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.
  • Make architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, continuous integration and continuous delivery, 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.

Desired Qualifications

  • Experience with cloud environments such as AWS, Azure, or Google Cloud and common platform services including storage, compute, identity and access management, and networking.
  • At least one of the listed AWS Professional certifications: Solutions Architect, DevOps Engineer, or Generative AI Developer.
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments.
  • Data engineering experience with Spark, Airflow or dbt, streaming, and data modeling; or a machine learning or data science background in feature engineering, experimentation, or model evaluation.
  • Experience with MLOps or LLMOps practices, including evaluation frameworks, model monitoring, and prompt management.
  • Experience integrating large language model solutions with enterprise systems through APIs, microservices, or event-driven architectures.
  • Experience operating within hybrid onshore/offshore teams.
  • Familiarity with security, privacy, and compliance considerations.

About the Company

Deloitte

Audits companies and advises on tax and technology

Deloitte audits companies and advises businesses and governments on tax, technology, and risk, and it is one of the Big Four, the world's four largest accounting firms. In 1849 its founder became the first independent auditor of a public company, Britain's Great Western Railway. Its auditors check companies' financial reports for errors and fraud before investors rely on them, while its consultants design strategy, install business software, and defend clients against cyberattacks. Clients pay fees for each audit or project, and each country's Deloitte firm is a separate business owned by its local partners. Deloitte was founded in London in 1845 and is based in New York.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$17.1M
Headquarters
New York, NY
Founded
1845

Recently Posted Jobs

Explore more opportunities at Deloitte

See more jobs