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Deloitte

Audits companies and advises on tax and technology

Lead Forward Deployed Engineer - Frontier GenAI

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 Anthropic, Google, or OpenAI frontier generative AI platforms, including hands-on experience with at least one of the listed products or capabilities: Claude API, Claude for Enterprise, tool use, extended thinking, Claude Code, Gemini API, Vertex AI Agent Builder, Grounding, Google Workspace integration, GPT-4o, Assistants API, Responses API, or OpenAI Agents SDK.
  • 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.
  • Ability to travel 50% on average, depending on assigned work and clients or industries served.

Responsibilities

  • Serve as the senior client-facing engineering partner for client product, data, and platform leaders, building trusted-advisor relationships.
  • Lead executive-level discovery, define success metrics for quality, latency, cost, adoption, and risk, and create a phased plan from prototype through production and scale.
  • Align executive sponsors, IT leadership, and business owners around a shared vision by navigating organizational complexity and influencing stakeholders.
  • Represent the forward-deployed engineering capability in client pursuits, executive briefings, and platform partner engagements, contributing to pipeline development and deal shaping.
  • Lead forward-deployed engineering pods of 2–5 onshore-anchored and offshore-supported engineers, owning execution, resource management, escalations, and overall delivery health.
  • Set delivery standards across the pod, including sprint cadences, stakeholder communication plans, risk management, and quality gates.
  • Coordinate multi-pod or multi-workstream engagements to ensure reliable architecture and a consistent client experience.
  • Mentor and develop junior forward-deployed engineers.
  • Architect and oversee delivery of large language model-enabled applications, including copilots, agentic workflows, assistants, and knowledge-search experiences using enterprise AI platforms.
  • Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls.
  • Govern end-to-end retrieval-augmented generation pipeline design, including ingestion, chunking, embedding, vector retrieval, and hybrid search, ensuring production-grade quality and scalability.
  • Define evaluation frameworks for quality, hallucination risk, safety, latency, cost, and governance, and ensure the pod meets agreed engineering quality standards.
  • Review and contribute to production-quality code.
  • Guide the architecture of data pipelines that power generative AI use cases.
  • Enforce strong data management, testing, continuous integration and continuous delivery, logging, versioning, and documentation practices.

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.
  • 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, or 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

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