AI Builder Jobs
AI Builder jobs are open across technology, finance, healthcare, and enterprise software, from entry-level to principal and staff, with specializations in LLM integration, agentic workflow design, and prompt engineering. Find a role that fits below and apply directly.
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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 : 12/10/2026Pay 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 29 AI Builder Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI Builder JobsAI Builder Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
What Employers Look For
The qualifications that appear most often in AI builder jobs.
- Hands-on experience building and deploying LLM-powered applications in production environments
- Proficiency with orchestration frameworks such as LangChain, LlamaIndex, or AutoGen
- Ability to design and implement retrieval-augmented generation pipelines end to end
- Experience with at least one major cloud AI platform including Azure OpenAI, AWS Bedrock, or Google Vertex AI
- Strong Python programming skills with familiarity in API integration and async workflows
- Bachelor's degree in computer science, engineering, or a related technical field, or equivalent practical experience
Tips for Your AI Builder Job Search
Showcase end-to-end AI systems you built
Hiring managers want to see complete pipelines, not isolated model experiments. Document a project from data ingestion through deployment, including how you handled evaluation, latency constraints, and failure modes. A GitHub repo with a working demo carries more weight than a resume bullet.
Tailor your resume to the stack listed
AI builder roles vary widely by tooling. One listing requires LangChain and RAG architecture, the next wants AutoGen and Azure OpenAI. Mirror the exact tool names from each job description in your resume so your application clears automated screening before a human ever reads it.
Apply early to roles that fit
Migrate Mate lists ai builder openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target roles by deployment environment
Filter openings by whether the team ships to cloud, on-premise, or edge environments. Your experience deploying containerized inference on AWS differs meaningfully from fine-tuning models on-device. Applying only where your deployment background matches the role reduces wasted interviews.
Prepare a system design answer for LLM pipelines
Most ai builder technical screens include an open-ended architecture question. Practice walking through your choices for chunking strategy, retrieval method, guardrails, and observability out loud. Interviewers are evaluating your reasoning process, not just whether you name the right framework.
Negotiate scope before negotiating compensation
AI builder offers often include ambiguous ownership over model selection and infrastructure decisions. Clarify during the offer stage whether you control tooling choices or inherit a fixed stack. Scope affects long-term career growth more than a small compensation difference at the same level.
AI Builder Jobs: Frequently Asked Questions
Which companies are hiring the most ai builders?
The companies hiring the most ai builders right now include Exiger, Salesforce, and Hello Patient, with the largest share of openings in California, New York, and Texas, based on current listings on Migrate Mate as of November 2026. Demand is concentrated in enterprise software, financial services, and healthcare technology.
How many ai builder jobs are remote?
About 81% of ai builder openings are fully remote or hybrid as of November 2026, reflecting the cloud-native nature of most AI development work. Sub-specializations focused on LLM integration and prompt engineering tend to offer the highest share of fully remote arrangements, while roles involving on-premise model deployment or hardware-adjacent inference work are more likely to require on-site presence.
How do you become a ai builder?
Start by building a working LLM-powered application from scratch and publishing it publicly. Learn a retrieval-augmented generation framework, connect it to a vector database, and document your architecture decisions. Then contribute to an open-source AI project or complete a cloud provider's generative AI certification to demonstrate you can ship production-grade systems, not just run notebooks.
How do you get hired as a ai builder with little experience?
Build a portfolio of two or three working projects that solve a real problem using an LLM API, even if the use case is narrow. Focus on demonstrating clean prompt design, error handling, and evaluation rather than model training. Apply to companies with internal AI tools teams where the bar for entry-level candidates is set by shipping speed and curiosity, not years of experience.
What does the ai builder interview process look like?
Most ai builder interviews start with a recruiter screen focused on your project background, followed by a technical screen where you walk through a past system you built or complete a take-home design task. Final rounds typically include a live coding or architecture session, a product thinking discussion about AI use cases, and a conversation with engineering or product leadership about your approach to building with uncertainty in AI outputs.
Where can I find and apply to ai builder jobs?
You can find and apply to ai builder jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your stack and experience level, then apply directly to each one that fits.
See All 29 AI Builder Jobs
Find roles that match your experience and apply in just a few clicks.
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