Genai Engineer Jobs
Genai Engineer jobs are open across technology, finance, healthcare, and enterprise software, from new-grad to staff and principal levels, with specializations in large language model development, retrieval-augmented generation, and AI agent systems. Find a role that fits from the openings below and apply directly.
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Showing 5 of 108+ Genai Engineer jobs
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience programming in Python or C++.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 3 years of experience testing, maintaining, or launching software products.
- 1 year of experience with software design and architecture.
- 1 year of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 5 years of experience with data structures/algorithms.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
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
- Write and test product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience programming in Python or C++.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 3 years of experience testing, maintaining, or launching software products.
- 1 year of experience with software design and architecture.
- 1 year of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 5 years of experience with data structures/algorithms.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
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
- Write and test product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains.
Genai Engineer Jobs by Experience Level
Top Cities Hiring Genai Engineers
Explore genai engineer openings in the cities hiring most right now.
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Find Genai Engineer JobsGenai Engineer Job Market
Who's Hiring
- Google17
- Capital One15
- Infosys6
- Youtube4
- Deloitte4
Top Industries Hiring
- Technology & Software12
- Accounting & Auditing3
- Electronics & Hardware3
- Banking & Financial Services3
- Investment & Asset Management3
What Employers Look For
The qualifications that appear most often in genai engineer jobs.
- Proficiency in Python and experience building or fine-tuning large language models
- Hands-on experience with LangChain, LlamaIndex, or comparable orchestration frameworks
- Familiarity with vector databases such as Pinecone, Weaviate, or pgvector
- Experience deploying AI applications on AWS, Azure, or Google Cloud platforms
- Understanding of prompt engineering, RAG architecture, and evaluation methods
- Bachelor's or master's degree in computer science, machine learning, or a related field
Tips for Your Genai Engineer Job Search
Quantify your model impact on your resume
Hiring managers for genai engineer roles want to see concrete outcomes, not just tool names. Replace vague bullets with measurable results: latency reductions, retrieval accuracy improvements, or cost-per-token decreases tied to your specific work.
Highlight RAG and fine-tuning projects separately
Retrieval-augmented generation and fine-tuning are distinct skill sets that appear as separate filters in many job descriptions. List them as individual line items so your resume surfaces in both kinds of targeted searches.
Filter openings by infrastructure stack
Many genai engineer postings require fluency in a specific cloud AI platform, such as AWS Bedrock, Azure OpenAI Service, or Vertex AI. Narrow your search by the stack you know best to avoid wasting applications on roles built around unfamiliar tooling.
Apply early to roles that fit
Migrate Mate lists genai 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 system design answer for LLM pipelines
Almost every genai engineer interview includes a system design round focused on production LLM architecture. Practice walking through prompt management, chunking strategy, embedding storage, and output evaluation before your first screen.
Negotiate with deployment complexity in mind
Offers for genai engineers vary based on whether the role involves model development, API integration, or full MLOps ownership. Clarify the deployment scope before accepting and use that complexity to anchor your compensation conversation.
Genai Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most genai engineers?
The companies hiring the most genai engineers right now include Google, Capital One, and Infosys, with the largest share of openings in California, New York, and Texas, based on current listings on Migrate Mate as of September 2026. Demand is concentrated in enterprise technology, financial services, and healthcare software.
How many genai engineer jobs are remote?
About 44% of genai engineer openings are fully remote or hybrid as of September 2026, making it one of the more distributed engineering roles in the market. Sub-specializations in prompt engineering, LLM API integration, and evaluation tooling tend to have the highest share of remote-eligible postings compared to roles requiring on-premise model training infrastructure.
How do you become a genai engineer?
Start by building a strong foundation in Python and machine learning fundamentals, then work through hands-on projects using open-source models from Hugging Face. Learn how to build RAG pipelines, experiment with fine-tuning smaller models, and deploy an end-to-end application to a cloud platform. Document your projects publicly so hiring managers can evaluate your actual output rather than just your credentials.
Can I get hired as a genai engineer without much experience?
Yes, entry-level genai engineer roles exist, particularly at startups and in product teams integrating third-party LLM APIs rather than training models from scratch. Candidates who have built and shipped a working genai application, even as a side project, consistently get more traction than those who list only coursework. Contributing to open-source LLM tooling or writing detailed technical walkthroughs of your builds also helps establish credibility quickly.
What does the genai engineer interview process look like?
Most genai engineer interview processes include an initial recruiter screen, a take-home or live coding assessment focused on building a small LLM-powered feature, and a technical panel covering system design for production AI pipelines. Some companies add a separate evaluation round where you critique or improve an existing prompt or retrieval setup. Culture and cross-functional fit interviews typically close the process before an offer is extended.
Where can I find and apply to genai engineer jobs?
You can find and apply to genai engineer jobs on Migrate Mate, which lists current openings from across the United States in one place. Find roles that match your skills and apply directly to each listing without being redirected to separate company portals or third-party sites.
See All 108+ Genai Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Genai Engineer Jobs