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Head of Anthropic Forward Deployed Engineering (FDE)

Published · Updated

Pay not postedUS · city not listed

Leads client-facing Anthropic FDE engagements as the technical authority while building and managing Lovelytics’ Anthropic FDE team and delivery practice.

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View posting at lovelytics

At a glance

Posted base pay

Not posted

The work

Leads the deployment team

Balance

  1. Mostly building
  2. Mixed
  3. Mostly pre-sales or support

Project stages

  1. Pre-sales
  2. Proof of concept (not covered)
  3. Implementation
  4. Operations (not covered)

Travel Up to 40%

Coding
Writes production code
Builds for
External customers
Level
Staff+
Role
People manager

What they ask for

Experience

  • 10+ yearssoftware engineering, AI engineering, machine learning, or data engineering

Background

  • Software engineering
  • Implementation and data engineering

Tools

  • Anthropic Claude
  • Model Context Protocol (MCP)
  • Databricks
  • LangGraph
  • LangChain
  • LlamaIndex
  • Python
  • Retrieval-Augmented Generation (RAG)

Less common in FDE jobs

  • Individual contributor or manager: People manager4%
  • Responsibility level: Staff+17%
  • Covers pre-sales24%

Share of US FDE postings that state each fact.

The job description from lovelytics

Posted by lovelytics on

Founded in 2017, Lovelytics has helped some of the most complex enterprises across industries such as Energy & Utilities, Media & Entertainment, Manufacturing and Retail & CPG, modernize their data and put AI to work, not in a deck, but in production. We move fast, stay close to the cutting edge, and care more about outcomes than optics.

Our work spans the full data and AI lifecycle: Data Strategy & Advisory, Data Engineering, Analytics & Visualization, Generative AI & ML, and Cloud Migration & Modernization — all delivered on Databricks, with deep partnerships across AWS, Azure, and GCP. To date, we've delivered over $2B in business value for Fortune 500 clients.

In the last year, Lovelytics has grown from 85 to 500+ people across the Americas, all while keeping the technically excellent, low-ego culture that makes the work worth doing, earning us a Best Places to Work recognition and a spot among Databricks' top partners.

Lovelytics is looking for a Head of Anthropic Forward Deployed Engineering to serve as both a hands-on client facing technical leader, as well as helping us build out and expand our Anthropic FDE team. This role would play the lead FDE role on Lovelytics’ Anthropic clients, and also lead the building and management of the FDE team at Lovelytics within the Anthropic practice.

The Head of Anthropic Forward Deployed Engineering is responsible for owning our technical leadership on projects, building a team of technical Anthropic experts, and supporting the development of Lovelytics’ delivery IP as it relates to Anthropic.

Primary Responsibilities

  • Serve as the lead architect and technical authority for all Anthropic client engagements.
  • Establish the foundation for Lovelytics’ Forward Deployed Engineering Practice and build the team needed to scale it effectively.
  • Design, build, and deploy enterprise AI applications leveraging Anthropic Claude and the broader Anthropic ecosystem.
  • Partner with clients to understand business objectives and translate them into scalable AI solution architectures.
  • Lead technical discovery sessions, architecture workshops, and solution design discussions with client stakeholders.
  • Establish technical standards, best practices, and reusable reference architectures for Anthropic implementations.
  • Develop reusable delivery and implementation methodologies to scale the Anthropic practice.
  • Support business development efforts through technical solutioning, client presentations, demonstrations, and proposal development in partnership with Lovelytics Anthropic GTM team.
  • Stay current on advancements in generative AI and continuously identify opportunities to improve delivery, automation, and client value.
  • Develop production-ready applications utilizing LLMs, Retrieval-Augmented Generation (RAG), AI agents, tool use, Model Context Protocol (MCP), and modern AI orchestration frameworks.
  • Architect secure integrations between AI applications, enterprise data platforms, APIs, and cloud infrastructure. — need to

Qualifications

  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field (or equivalent experience).
  • 10+ years of experience in software engineering, AI engineering, machine learning, or data engineering.
  • Demonstrated experience architecting and deploying enterprise data client engagements while leading a team.
  • Experience with Anthropic Claude, Model Context Protocol (MCP), Databricks, LangGraph, LangChain, LlamaIndex, or similar AI technologies is strongly preferred.
  • Hands-on experience with Cowork and Code, including designing, building, and deploying AI workflows and enterprise AI applications.
  • Expertise in Python and modern software engineering practices.
  • Proven ability to build applications using large language models (LLMs), including prompt engineering, RAG, AI agents, tool calling, and orchestration frameworks.
  • Strong understanding of APIs, distributed systems, authentication, and enterprise application architecture.
  • Experience in a client-facing consulting, professional services, solutions engineering, or technical advisory role.
  • Excellent communication and presentation skills with the ability to communicate effectively with both technical and executive audiences.
  • Willingness to travel and work on client sites (20-40%)

Lovelytics is an Equal Opportunity Employer. This means you don’t have to worry about whether your application process will be fair. We consider all applicants without regard to race, color, religion, age, ancestry, ethnicity, gender, gender identity, gender expression, sexual orientation, veteran status, or disability.

View posting at lovelytics

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Pay and conditions

Posted pay
Pay not posted
Location
US · city not listed
Travel
Up to 40%
Experience requirements
  • 10+ years: software engineering, AI engineering, machine learning, or data engineering (required)