Genai Software Engineer Jobs
Genai Software Engineer jobs are open across technology, finance, healthcare, and enterprise software, from new-grad to principal and staff level, with specializations in large language model fine-tuning, retrieval-augmented generation, and agentic system design. Find a role that fits from the openings below and apply directly.
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Showing 5 of 47+ Genai Software Engineer jobs
Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 5 years of experience in a technical leadership role; overseeing projects, with 3 years of experience in a people management, supervision/team leadership role.
- 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience with computer vision learning techniques, machine learning algorithms (supervised and unsupervised learning, deep learning, reinforcement learning), generative AI, or applied AI applications
Preferred qualifications:
- Master's degree or PhD in Computer Science, or a related technical field.
- 5 years of experience with one or more of the following: Computer Vision, Reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- Multiple research publications in top CV/ML conferences (e.g., CVPR/ICCV/ECCV/NIPS/ICLR).
- Experience working in large-sized engineering and cross-functional teams.
- Expertise in modeling with TensorFlow, JAX, etc.
- Excellent people management and communication skills.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
As an Engineering Manager, you will use your extensive Machine Learning and Computer Vision experience to lead the team in designing and building the freshest and most detailed 3D navigation map using sensor data (e.g., imagery, vehicle telemetry, location data, authoritative data, etc.), large ML models, and AI techniques to create new structured geospatial data and transformative user experiences for 2 billion+ users globally.
The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Take end-to-end ownership of converting complex imagery, location, and sensor data into precise geometries to power Geo’s next generation navigation products. Translate ambiguous input data challenges into clear algorithmic, ML, GenAI formulations, brainstorming directly with product, UX, and engineering to define the optimal visual experience and iterate towards scalable solutions.
- Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
- Set clear expectations with individuals based on their level and role, aligned with broader organizational goals. Meet regularly with individuals to discuss performance, development, feedback and coaching.
- Develop the long-term technical outlook and roadmap, meeting anticipated future requirements and infrastructure needs.
- Design, guide and vet system designs, and write product or system development code to solve ambiguous problems. Conduct code reviews and provide feedback ensuring best practices.
Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 5 years of experience in a technical leadership role; overseeing projects, with 3 years of experience in a people management, supervision/team leadership role.
- 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience with computer vision learning techniques, machine learning algorithms (supervised and unsupervised learning, deep learning, reinforcement learning), generative AI, or applied AI applications
Preferred qualifications:
- Master's degree or PhD in Computer Science, or a related technical field.
- 5 years of experience with one or more of the following: Computer Vision, Reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- Multiple research publications in top CV/ML conferences (e.g., CVPR/ICCV/ECCV/NIPS/ICLR).
- Experience working in large-sized engineering and cross-functional teams.
- Expertise in modeling with TensorFlow, JAX, etc.
- Excellent people management and communication skills.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
As an Engineering Manager, you will use your extensive Machine Learning and Computer Vision experience to lead the team in designing and building the freshest and most detailed 3D navigation map using sensor data (e.g., imagery, vehicle telemetry, location data, authoritative data, etc.), large ML models, and AI techniques to create new structured geospatial data and transformative user experiences for 2 billion+ users globally.
The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Take end-to-end ownership of converting complex imagery, location, and sensor data into precise geometries to power Geo’s next generation navigation products. Translate ambiguous input data challenges into clear algorithmic, ML, GenAI formulations, brainstorming directly with product, UX, and engineering to define the optimal visual experience and iterate towards scalable solutions.
- Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
- Set clear expectations with individuals based on their level and role, aligned with broader organizational goals. Meet regularly with individuals to discuss performance, development, feedback and coaching.
- Develop the long-term technical outlook and roadmap, meeting anticipated future requirements and infrastructure needs.
- Design, guide and vet system designs, and write product or system development code to solve ambiguous problems. Conduct code reviews and provide feedback ensuring best practices.
Genai Software Engineer Jobs by Experience Level
See All 47 Genai Software Engineer Jobs
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Find Genai Software Engineer JobsGenai Software Engineer Job Market
Who's Hiring
- Google12
- EY3
- Visa3
- Youtube3
- Capital One3
Top Industries Hiring
- Technology & Software
- Manufacturing
- Banking & Financial Services
What Employers Look For
The qualifications that appear most often in genai software engineer jobs.
- Proficiency in Python and experience with LLM APIs such as OpenAI, Anthropic, or open-source models
- Hands-on experience building or deploying retrieval-augmented generation pipelines
- Familiarity with vector databases such as Pinecone, Weaviate, Chroma, or pgvector
- Experience with orchestration frameworks including LangChain, LlamaIndex, or semantic kernel
- Strong foundation in machine learning concepts, model evaluation, and prompt engineering
- Bachelor's or master's degree in computer science, machine learning, or a related engineering field
Tips for Your Genai Software Engineer Job Search
Tailor your resume to model stacks
Recruiters scanning genai engineer resumes look for specific model families and orchestration frameworks. Name the exact tools you've worked with, such as LangChain, LlamaIndex, or OpenAI APIs, and tie each to a concrete output like latency reduction or accuracy improvement.
Show evaluation benchmarks you've built
Hiring teams increasingly ask how candidates measure model quality beyond user feedback. If you've built eval harnesses, defined ground-truth datasets, or run A/B experiments on prompt variants, describe that process explicitly. Many applicants skip this and it differentiates you quickly.
Apply early to roles that fit
Migrate Mate lists genai software engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target job descriptions by deployment context
Some roles focus on inference optimization and cost control, others on prompt engineering pipelines, and others on RAG architecture for enterprise search. Filter openings by the deployment context closest to your experience so your application speaks directly to what the team is actually building.
Prepare a live demo or notebook walkthrough
Technical screens for genai roles often move faster than traditional coding rounds. Having a Jupyter notebook or hosted demo that shows a real RAG pipeline, fine-tuned model, or agent loop lets you anchor the conversation in working code rather than abstract explanations.
Negotiate scope before you negotiate pay
Genai engineering roles vary widely in autonomy, model access, and infra ownership. Before accepting an offer, confirm whether you control model selection, whether the team runs evals consistently, and what the compute budget looks like. Scope mismatches surface within the first month.
Genai Software Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most genai software engineers?
The companies hiring the most genai software engineers right now include Google, EY, and Visa, with the largest share of openings in California, Virginia, and Texas, based on current listings on Migrate Mate as of September 2026. Demand is concentrated in enterprise software, cloud infrastructure, and financial services firms building internal AI products.
How many genai software engineer jobs are remote?
About 73% of genai software engineer openings are fully remote or hybrid as of September 2026, making it one of the more remote-accessible engineering specializations available today. Roles focused on prompt engineering, RAG pipeline development, and model evaluation tend to be the most location-flexible, while positions tied to on-premise inference infrastructure or regulated data environments more often require on-site presence.
How do you become a genai software engineer?
Start by building a strong Python foundation and getting comfortable calling LLM APIs to complete real tasks. From there, learn the core patterns: prompt engineering, retrieval-augmented generation, and agent design using a framework like LangChain or LlamaIndex. Build at least one end-to-end project you can demo, document your eval methodology, and deploy something publicly. Contributions to open-source genai tooling and published notebooks accelerate credibility significantly.
Can you get a genai software engineer job with little experience?
Yes, entry-level genai software engineer roles exist, particularly at startups and in companies building internal AI tools for the first time. The most effective path is a portfolio of working projects that demonstrate you can move from a problem statement to a deployed solution using modern LLM tooling. Employers hiring junior genai engineers typically care more about your ability to learn fast and ship quickly than about years of experience in the field.
What does the genai software engineer interview process look like?
Most genai software engineer interviews include a recruiter screen, a technical phone round focused on Python and ML fundamentals, and a take-home or live coding exercise involving an LLM task such as building a RAG pipeline or evaluating model outputs. A system design round covering AI infrastructure, latency, and cost tradeoffs is common for mid-level and senior roles. Final rounds often include a presentation of a past project and a conversation with engineering leadership about model strategy.
Where can I find and apply to genai software engineer jobs?
You can find and apply to genai software engineer jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your experience and the specific genai domains you work in, then apply directly to each listing. The openings on this page are updated regularly, so checking back when your search is active gives you access to the latest opportunities.
See All 47 Genai Software Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Genai Software Engineer Jobs