Forward Deployed AI Engineer Jobs
Forward Deployed AI Engineer jobs are open across enterprise software, defense, healthcare, and fintech, from mid-level to staff and principal, with specializations in LLM integration, AI product deployment, and customer-facing ML systems. Scan the live roles below and apply to whichever ones fit.
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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 PRINCIPAL ENGINEER –AI PLATFORMS, FORWARD DEPLOYED ENGINEERING and AI BUILDER EXPERIENCE
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.
A role with Target’s AI Platform organization means the opportunity to build and evolve the foundational capabilities that enable teams across Target to develop, deploy, and operate AI-powered products and experiences at enterprise scale. Our teams build platforms, frameworks, and developer experiences that make advanced AI technologies accessible, reliable, and scalable for engineers across the organization.
As a Principal Engineer – AI Builder Experience and Forward Deployed Engineering, you will provide technical leadership for how engineering teams across Target build, integrate, deploy, and operate AI-powered applications. You will work at the intersection of AI platform engineering, developer experience, and forward deployed engineering, partnering directly with product and engineering teams to accelerate complex and high-value AI initiatives while shaping reusable capabilities for the broader engineering community.
You will help architect and deliver production-grade AI solutions, including agentic and LLM-powered applications, while establishing scalable patterns for model and agent integration, enterprise context, evaluation, observability, deployment, and production operations. You will bring deep platform expertise directly to engineering teams, helping them navigate complex technical challenges and successfully move AI solutions from experimentation into production.
A critical part of this role is translating real-world implementation experience into improvements to the AI platform. You will identify recurring challenges and patterns across forward deployed engagements and turn those learnings into reusable APIs, SDKs, frameworks, developer tooling, reference architectures, and self-service platform capabilities. Through this feedback loop, you will help reduce bespoke engineering and continuously improve the experience for the next generation of AI builders.
You will also provide technical leadership for the end-to-end AI developer experience, including onboarding, development, experimentation, testing, evaluation, debugging, deployment, and observability. You will partner closely with platform engineering, product, architecture, and application teams to influence platform roadmaps, establish engineering standards, and create reference implementations that enable teams to adopt AI capabilities effectively and responsibly at scale.
Given the pace of change in AI, you will stay current on emerging technologies and engineering approaches, evaluate and recommend new frameworks and tooling, publish learnings and reusable patterns, mentor senior engineers, and influence technical direction across the broader AI engineering ecosystem. We utilize Agile principles, follow best-practice software design, participate in code reviews, and create maintainable, well-tested codebases with relevant documentation.
Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.
About you:
- MS or PhD in Computer Science, Engineering, Mathematics, Statistics, or another quantitative discipline or equivalent industry experience
- 8 plus years of experience designing, building, and operating large-scale software platforms, developer platforms, AI/ML systems, or distributed systems in production environments
- Strong hands-on software engineering experience and demonstrated ability to architect and deliver production-grade systems
- Experience designing and delivering AI applications, including LLM-powered or agentic systems, and understanding of model integration, context and retrieval patterns, tool integration, evaluation, and production operations
- Experience building developer-facing capabilities such as APIs, SDKs, frameworks, libraries, developer tooling, templates, or self-service platform experiences
- Experience with modern AI engineering and platform technologies, including model APIs, agent development frameworks, evaluation and observability tooling, cloud platforms, containers, orchestration, CI/CD, and operational monitoring
- Strong understanding of distributed system design, platform architecture, scalability, reliability, performance optimization, security, and production deployment considerations
- Demonstrated ability to partner directly with engineering and product teams, understand complex implementation challenges, and translate those challenges into scalable technical solutions and reusable platform capabilities
- Ability to operate effectively across the full engineering lifecycle, from architecture and prototyping through implementation, production deployment, and operational maturity
- Ability to translate ambiguous business and engineering problems into clear technical approaches and create strong technical documentation, reference architectures, narratives, and recommendations for a range of audiences
- Excellent communication and influencing skills, with demonstrated ability to establish technical direction and drive alignment across engineering teams and organizational boundaries
- Proven ability to mentor and provide technical leadership to senior engineers while influencing architecture and engineering standards without direct authority
- Self-driven and results-oriented, with strong ownership, sound technical judgment, and the ability to balance near-term delivery with long-term platform scalability
- Collaborative team player with experience working effectively across functions, organizations, and geographies, and with a demonstrated commitment to continuous learning and knowledge sharing
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_FAmericans 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 : 12/10/2026See All 1,194+ Forward Deployed AI Engineer Jobs
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Find JobsForward Deployed AI Engineer Job Market
Who's Hiring
- Databricks67

- Palantir Technologies38

- Amazon Web Services36

- Deloitte33

- Accenture26

Top Industries Hiring
- Technology & Software192
- Consulting & Professional Services31
- Artificial Intelligence23
- Staffing & Recruiting14
- Investment & Asset Management10
What Employers Look For
The qualifications that appear most often in forward deployed AI engineer jobs.
- Experience deploying large language models or generative AI systems in production environments
- Proficiency in Python and familiarity with common ML frameworks such as PyTorch or TensorFlow
- Ability to work directly with enterprise customers to scope and implement AI solutions
- Experience with API integration, cloud platforms, and infrastructure tooling in customer-facing contexts
- Strong written and verbal communication skills for translating technical concepts to non-technical stakeholders
- Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience
Tips for Your Forward Deployed AI Engineer Job Search
Show deployment outcomes not model training
Your resume should lead with what you shipped and who used it. Hiring managers for forward deployed ai engineer roles care more about production impact at customer sites than model accuracy benchmarks or academic datasets.
Highlight cross-functional communication experience
These roles sit at the intersection of engineering and customer success. Show concrete examples where you translated a customer's technical constraint into a working AI solution, not just that you can write clean code.
Target companies with dedicated deployment teams
Filter openings by companies that run a dedicated forward deployment or field AI function rather than folding the role into generic software engineering. Those postings describe customer-facing work explicitly and signal a real career path.
Apply early to roles that fit
Migrate Mate lists forward deployed ai engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a live integration demo for interviews
Many forward deployed ai engineer interviews include a technical exercise where you connect a model or API to a customer-like environment in real time. Walk through a past integration you built and document it in a shareable format before your first screen.
Negotiate scope alongside compensation
When you receive an offer, clarify which customer segments you will support, how much independent scoping authority you will have, and what the escalation path looks like. These details affect daily work quality more than title does.
Forward Deployed AI Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most forward deployed ai engineers?
The companies hiring the most forward deployed ai engineers right now include Databricks, Palantir Technologies, and Amazon Web Services, with the largest share of openings in California, New York, and Texas, based on current listings on Migrate Mate as of November 2026. Enterprise AI software vendors and defense-adjacent technology companies consistently account for the bulk of these openings.
How many forward deployed ai engineer jobs are remote?
About 65% of forward deployed ai engineer openings are fully remote or hybrid as of November 2026, though the nature of the role means on-site customer engagement is often expected at some frequency. Sub-specializations focused on internal tooling or platform-layer work tend to offer the highest share of fully remote arrangements.
How do you become a forward deployed ai engineer?
Start by building hands-on experience deploying AI or ML systems in production, not just training models. Develop strong Python skills and work through real integration projects using public APIs or open-source models. Then build a portfolio of customer-facing or cross-functional deployments, contribute to technical documentation, and apply to roles at companies with a named forward deployment or field AI function.
Can you get hired as a forward deployed ai engineer without experience?
It is possible to break in without direct experience if you can demonstrate deployment instincts through project work. Build and document an end-to-end AI integration, even a personal or open-source one, that shows you can scope a problem, connect a model to a real data source, and hand it off to a non-technical user. Some companies also hire into associate or rotation programs that feed into the forward deployed function.
What does the forward deployed ai engineer interview process look like?
The process typically starts with a recruiter screen followed by a technical phone interview focused on ML fundamentals and system design. A take-home or live coding exercise involving API integration or model deployment usually comes next. Final rounds often include a customer scenario exercise where you are asked to scope a solution, present it, and field objections from interviewers playing the role of a customer stakeholder.
Where can I find and apply to forward deployed ai engineer jobs?
You can find and apply to forward deployed ai engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your background and apply directly to each one that fits your experience and target industry.
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