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Target

Lead Forward Deployed Engineer (FDE) - AI Platforms (ML, LLMs, APIs, ML Ops)

Target is hiring a Lead Forward Deployed Engineer (FDE) - AI Platforms (ML, LLMs, APIs, ML Ops) for a remote role open to applicants in United States. It pays $132k-$238k a year and Level rates it ; you can apply on Target.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this forward deployed engineer role: the daily work is on AI products, without building the model.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include MLOps.
  • Level lists 14,000+ other open roles at Target.
  • The role was posted in the last few days.

AI in this role

ml-ops
The pay range is $132,000.00 - $238,000.00

Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.

JOIN TARGET AS A LEAD ENGINEER – FORWARD DEPLOYED ENGINEERING - AI PLATFORMS


About Us:

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.


As a Lead Forward Deployed Engineer - AI Platforms (FDE), you will help accelerate the adoption of Target's enterprise AI platform by working with product and engineering teams to solve complex technical challenges, enable platform capabilities, and help teams build and operate production-grade AI applications. You will operate at the intersection of AI engineering, platform engineering, and product development bringing technical expertise in software architecture, distributed systems, LLMs, and agentic systems. You will combine hands-on engineering with technical guidance, solution architecture, and development of reusable tools and solutions that improve how teams adopt and use the enterprise AI platform


A key part of this role is learning from real-world implementations and using those insights to improve the broader AI platform. You will collaborate across engineering teams to identify recurring challenges, address adoption friction, and help translate successful implementation patterns into scalable platform capabilities.


As a Lead FDE Engineer, you bring broad technical expertise and help guide complex engineering efforts across teams and systems. You can independently design and implement production-grade architectures while improving the effectiveness of others through technical guidance, engineering practices, and collaborative problem-solving. You help teams navigate architectural tradeoffs, raise engineering quality, and connect technical decisions to long-term platform and product outcomes.


As a Lead Engineer within Forward Deployed Engineering, you’ll:


  • Lead complex technical engagements that accelerate enterprise AI platform adoption, combining solution architecture, hands-on engineering, and technical guidance to help teams move from experimentation to production
  • Design, build, and productionize AI solutions, reference implementations, technical tooling, and platform-support capabilities using LLMs, agentic architectures, enterprise context and retrieval, model APIs, and tool integrations
  • Guide technical design and implementation across engineering efforts, helping teams navigate complex architectural decisions, troubleshoot challenges, and develop scalable, maintainable solutions
  • Apply software engineering and distributed systems expertise to improve the reliability, security, performance, observability, and op readiness of production AI systems
  • Identify recurring implementation challenges, integration gaps, and platform limitations, collaborating with platform engineering to develop reusable patterns, APIs, SDKs, frameworks, and shared capabilities
  • Help establish and improve engineering practices across engagements - including architecture reviews, code quality, testing, evaluation, deployment, and prod ops
  • Collaborate across product, engineering, and platform teams to evaluate technical approaches, share implementation learnings, and improve how teams adopt and use enterprise AI capabilities

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.


About you:

  • 4-year degree or equivalent experience
  • 5+ years of software development experience with strong hands-on engineering and programming skills
  • Expertise in software architecture, design, distributed systems, APIs, cloud-native technologies and modern engineering practices
  • Demonstrated proficiency programming in Java, Python, Koltin, etc.
  • Hands-on experience building and productionizing AI apps using LLMs, agentic architectures, model APIs, retrieval/context patterns, tool integration and evaluation frameworks
  • Demonstrated ability to lead complex technical initiatives from design through production, guide architectural decisions, and navigate ambiguous engineering challenges across teams or systems
  • Experience with production engineering practices, including CI/CD, testing, observability, reliability, performance, security, and ops
  • Experience developing reusable engineering patterns, technical tooling, reference implementations, APIs, SDKs, or platform capabilities that improve platform adoption and engineering efficiency
  • Ability to provide technical guidance, influence engineering decisions, and improve engineering practices through collaboration, architecture reviews, and knowledge sharing
  • Effective communication and technical judgment, with the ability to evaluate tradeoffs and collaborate across product, engineering, and platform teams
  • Maintains technical knowledge within areas of expertise and stays current with rapidly evolving AI and software engineering technologies through formal training and self-directed learning.

This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click here if you are curious to learn more about Minnesota.

This position may be considered for a Remote or Hybrid (known internally at Target as "Flex for Your Day") work arrangement based on Target's needs. A Remote work arrangement means the team member works full-time from home or an alternate location that's not a Target location, does not have a desk at a Target location and may travel to HQ up to 4 times a year. A Hybrid/Flex for Your Day work arrangement means the team member's core role may be performed either remote or onsite at a Target location depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target.

Benefits Eligibility

Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_E

Americans with Disabilities Act (ADA)

In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.

Application deadline is : 12/10/2026

How we rate this

Lead Forward Deployed Engineer (FDE) - AI Platforms (ML, LLMs, APIs, ML Ops) at Target rates 67 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML Ops

Also common in forward deployed engineer jobs at this level

Pay

This job starts at
$132k
Typical forward deployed engineer job
$180k

This posting starts 27% below the typical forward deployed engineer job. See forward deployed engineer jobs

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Describe a typical day in a role like this one: which parts run through AI directly?
  3. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: ML Ops. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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