Generative AI Associate Jobs
Generative AI Associate jobs are open across technology, finance, healthcare, and media, from entry-level to senior associate, with specializations in prompt engineering, model fine-tuning, and AI product development. See the openings below and apply to the ones that match your experience.
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Showing 5 of 186+ Generative AI Associate jobs
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Chicago, IL, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 5 years of experience with software development using Python or similar coding languages.
- Experience architecting AI systems on cloud platforms (e.g., GCP).
- Experience taking production-grade AI-driven solutions from conception to launch for customers.
- Experience leading technical discovery sessions with customers.
- Experience building pipelines for structured and unstructured data using both vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise AI solutions.
Preferred qualifications:
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and patterns (e.g., ReAct, self-reflection, hierarchical delegation).
- Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
About the job
As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you will function as an innovator-builder, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.
This role is designed for high-agency engineers with a founder’s mindset. You will address blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol (MCP) servers) that drive measurable return on investment.
- Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team.
- Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
- Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Chicago, IL, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 5 years of experience with software development using Python or similar coding languages.
- Experience architecting AI systems on cloud platforms (e.g., GCP).
- Experience taking production-grade AI-driven solutions from conception to launch for customers.
- Experience leading technical discovery sessions with customers.
- Experience building pipelines for structured and unstructured data using both vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise AI solutions.
Preferred qualifications:
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and patterns (e.g., ReAct, self-reflection, hierarchical delegation).
- Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
About the job
As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you will function as an innovator-builder, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.
This role is designed for high-agency engineers with a founder’s mindset. You will address blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol (MCP) servers) that drive measurable return on investment.
- Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team.
- Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
- Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
Generative AI Associate Jobs by Experience Level
See All 186+ Generative AI Associate Jobs
Find roles that match your experience and apply in just a few clicks.
Find Generative AI Associate JobsGenerative AI Associate Job Market
Who's Hiring
- Innodata30
- Google16
- TikTok13
- Amazon Web Services10
- Meta7
Top Industries Hiring
- Technology & Software23
- Artificial Intelligence3
- Distribution & Wholesale2
- Retail1
- Law & Legal Services1
What Employers Look For
The qualifications that appear most often in generative AI associate jobs.
- Hands-on experience with large language models such as GPT or LLaMA
- Proficiency in Python and machine learning frameworks including PyTorch or TensorFlow
- Experience with prompt engineering, fine-tuning, or retrieval-augmented generation pipelines
- Bachelor's degree in computer science, data science, or a related technical field
- Familiarity with vector databases and embedding-based search systems
- Ability to evaluate model outputs for accuracy, bias, and safety using structured methodologies
Tips for Your Generative AI Associate Job Search
Tailor your resume to model types
Hiring managers for generative AI roles scan for specific model families, such as LLMs, diffusion models, or multimodal systems. Name the architectures you've worked with directly, not just 'AI experience', so your resume surfaces in filtered searches.
Show output, not just process
Generative AI associate candidates who demonstrate shipped outputs, a fine-tuned model, a deployed prompt pipeline, a working RAG system, outperform those who list coursework. Even a public GitHub repo or a Hugging Face project card signals hands-on capability.
Apply early to roles that fit
Migrate Mate lists generative ai associate openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter by tech stack, not just title
Job titles vary wildly in this field. Search for the tools you know, LangChain, OpenAI API, vector databases, retrieval-augmented generation, alongside the title to find openings where your actual skills are what the team needs.
Prepare for a technical take-home
Many generative AI associate interviews include a take-home where you build or evaluate a small pipeline under a time constraint. Practice scoping a working prototype quickly and writing a short evaluation memo explaining your design tradeoffs.
Negotiate on scope, not just comp
In generative AI roles, what models you can access and whether you can publish research or open-source work matters as much as title. Ask directly about model access, compute budget, and publication policy before accepting an offer.
Generative AI Associate Jobs: Frequently Asked Questions
Which companies are hiring the most generative ai associates?
Innodata, Google, and TikTok are hiring the most generative ai associates right now, with openings concentrated in California, Texas, and New York, based on current listings on Migrate Mate as of November 2026. Demand is especially high at companies building internal AI tooling, foundation model labs, and enterprise software platforms integrating AI features.
How many generative ai associate jobs are remote?
About 79% of generative ai associate openings are fully remote or hybrid as of November 2026, reflecting the collaborative but asynchronous nature of much AI development work. Roles focused on prompt engineering, model evaluation, and AI content quality review tend to be the most remote-friendly, while positions tied to on-premises compute clusters or hardware labs more often require on-site presence.
How do you become a generative ai associate?
Start by building foundational skills in Python and machine learning, then focus specifically on large language model tooling such as the OpenAI API, Hugging Face Transformers, and LangChain. Complete a hands-on project you can show publicly, a fine-tuned model, a retrieval-augmented generation pipeline, or a prompt evaluation framework. Apply to associate and junior AI roles at companies actively building generative AI products, and use O*NET to understand the full skill profile employers expect for this occupation.
Can I get a generative ai associate job with little or no experience?
Yes, but you need demonstrated output in place of work history. Build at least one public project using an LLM API, fine-tuning workflow, or RAG system and document your design decisions clearly. Many hiring teams for associate roles care more about your ability to work with current tooling than the number of years on your resume, so a strong GitHub portfolio or Hugging Face model card can substitute effectively for prior employment.
What does the generative ai associate interview process look like?
The process typically includes an initial recruiter screen, a technical phone or video interview covering Python, ML fundamentals, and your project experience, and a take-home assignment where you build or evaluate a small generative AI pipeline. Final rounds often include a system design discussion focused on how you would architect a production-ready AI feature, followed by a team culture or cross-functional fit conversation with product or engineering leads.
Where can I find and apply to generative ai associate jobs?
You can find and apply to generative ai associate jobs on Migrate Mate, which lists current openings from across the United States. Search for roles that match your skills and background, then apply directly to each listing that fits. All active openings are shown on this page so you can move quickly when a strong match appears.
See All 186+ Generative AI Associate Jobs
Find roles that match your experience and apply in just a few clicks.
Find Generative AI Associate Jobs