Generative AI Engineer Jobs
Generative AI Engineer jobs are open across tech, financial services, healthcare, and media, from new-grad to staff and principal levels, with specializations in large language model fine-tuning, retrieval-augmented generation, and multimodal AI systems. Find a role that fits from the openings below and apply directly.
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Showing 5 of 184+ Generative AI Engineer jobs
About the role
Invonto is a technology company focused on digital transformation, AI, product innovation, and custom software development. We work with organizations to build and improve real-world digital products, from business applications to cloud-based platforms.
We’re looking for an experienced Generative AI Engineer who can turn emerging AI capabilities into practical applications and business solutions.
You’ll work on real-world projects involving large language models, AI-powered applications, intelligent automation, and enterprise integrations. This role is well suited for an engineer who enjoys both exploring new AI technologies and building reliable software around them.
What You’ll Do
- Design and develop AI-powered applications and solutions using generative AI and large language models
- Build custom AI solutions using self-hosted LLM as well as frontier models
- Develop AI capabilities including conversational assistants, intelligent search, document processing, summarization, content generation, and workflow automation
- Design and implement RAG solutions, embeddings, vector search, and AI-powered knowledge systems
- Develop and integrate AI agents and agentic workflows where appropriate
- Integrate AI capabilities with enterprise applications, APIs, databases, and business systems
- Design and evaluate prompts, model configurations, AI workflows, and responses
- Evaluate AI applications for accuracy, reliability, performance, and cost
- Develop prototypes and proof-of-concepts and help move successful solutions into production
- Work with structured and unstructured data to support AI applications
- Collaborate with developers, designers, project managers, and business stakeholders to translate business needs into practical AI solutions
- Contribute to technical architecture and implementation decisions
- Stay current with rapidly evolving AI models, tools, frameworks, and development practices
- Apply responsible AI practices with attention to data privacy, security, accuracy, and appropriate human oversight
What We’re Looking For
- 3+ years of professional software development, AI engineering, or related experience
- Hands-on experience building applications using Generative AI and large language models
- Strong programming experience with Python and/or JavaScript/TypeScript
- Strong understanding of LLMs, prompt engineering, embeddings, vector databases, and RAG
- Experience building REST APIs
- Experience working with databases and structured and unstructured data
- Experience integrating AI capabilities into applications or business workflows
- Understanding of software development lifecycle and engineering best practices
- Ability to evaluate AI-generated results and troubleshoot issues involving accuracy, reliability, latency, and cost
- Strong problem-solving and analytical skills
- Ability to communicate effectively with both technical and non-technical team members
- Ability to work independently as well as collaboratively
- Curiosity and willingness to continuously learn as AI technologies evolve
- Bachelor’s degree in Computer Science, Engineering, AI/ML, or a related field from a U.S. college or university
Nice to Have
Experience with:
- AI agents and agentic workflows
- LangChain, LangGraph, Semantic Kernel, or similar AI frameworks
- Vector databases such as PGVector and Pinecone
- AI evaluation and testing frameworks
- Fine-tuning or adapting AI models
- Multimodal AI, computer vision, or speech technologies
- AWS and/or Azure
- Docker and modern cloud development
- GitHub Copilot, Claude, Cursor, or other AI-assisted development tools
- Enterprise application integration
- CI/CD and DevOps practices
What We Offer
- 85,000–110,000 salary
- Health benefits
- Paid time off
- Flexible work environment
- Opportunity to work on real-world AI and digital transformation projects
- Exposure to emerging AI models, tools, frameworks, and cloud technologies
- Opportunities to work across different industries and business problems
- A collaborative environment with opportunities to learn and grow
Important Employment Information
This is a direct-hire position. We do not accept agency, C2C, or third-party submissions.
Candidates must be residing in the USA. Candidates must be U.S. Citizen or Permanent Resident. We are unable to provide visa sponsorship or accept OPT candidates for this position.
If you’re excited about AI, enjoy turning emerging technology into practical solutions, and want to work on applications that solve real business problems, we’d love to hear from you.
Apply today to join the Invonto team.
Job Type: Full-time
Pay: $85,000.00 - $110,000.00 per year
Benefits:
- Flexible schedule
- Health insurance
- Paid time off
- Tuition reimbursement
Application Question(s):
- Are you a US Citizen or Permanent Resident, as required for this role?
Experience:
- Python Flask: 2 years (Required)
- Dataset preparation: 3 years (Required)
- Python: 5 years (Required)
- API Development: 2 years (Required)
- AI development: 5 years (Required)
- Generative AI: 2 years (Required)
- PyTorch: 2 years (Preferred)
Work Location: Hybrid remote in Bridgewater, NJ 08807
Generative AI Engineer Jobs by Experience Level
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Find Generative AI Engineer JobsGenerative AI Engineer Job Market
Who's Hiring
- Innodata30
- Google19
- TikTok13
- Meta11
- Amazon Web Services9
Top Industries Hiring
- Technology & Software26
- Artificial Intelligence3
- Distribution & Wholesale2
- Retail1
- Law & Legal Services1
What Employers Look For
The qualifications that appear most often in generative AI engineer jobs.
- Proficiency in Python and deep learning frameworks such as PyTorch or JAX
- Hands-on experience fine-tuning or prompting large language models like GPT, Llama, or Gemini
- Experience building and deploying retrieval-augmented generation pipelines
- Familiarity with model serving infrastructure including APIs, containerization, and cloud platforms
- Bachelor's or master's degree in computer science, machine learning, or a related field
- Understanding of evaluation frameworks, safety considerations, and responsible AI practices
Tips for Your Generative AI Engineer Job Search
Tailor your resume to model type
Recruiters and hiring managers scan for specific model families you've worked with. Call out LLMs, diffusion models, or multimodal architectures by name in your experience bullets, not just 'generative AI,' so your resume matches the exact language in job listings.
Show production deployments, not prototypes
Most generative AI engineer roles want evidence of systems that shipped, not Jupyter notebooks. Quantify throughput, latency improvements, or cost reductions from a deployed endpoint. Side projects count if they serve real users and you can describe the infrastructure.
Filter openings by stack before applying
Job descriptions vary widely: some teams run everything on proprietary APIs, others want low-level PyTorch experience. Read the technical requirements carefully and match your application to roles where your stack overlaps at least two thirds of what they list.
Apply early to roles that fit
Migrate Mate lists generative 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 for system design around inference
Technical interviews at companies building generative AI products often focus on inference pipeline design: batching strategies, model serving frameworks like vLLM or TGI, and cost-per-token tradeoffs. Practicing these scenarios is more valuable than re-reading model architecture papers.
Negotiate scope before salary
Generative AI roles vary enormously in autonomy. Before discussing compensation, clarify whether you own the full ML lifecycle or support a research team. Roles with more ownership over architecture and deployment decisions typically have stronger leverage for negotiating total compensation.
Generative AI Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most generative ai engineers?
The companies hiring the most generative ai engineers right now include Innodata, Google, and TikTok, with the largest share of openings in California, Texas, and New York, based on current listings on Migrate Mate as of November 2026. Demand is concentrated at companies building AI-native products as well as enterprises integrating generative AI into existing platforms.
How many generative ai engineer jobs are remote?
About 79% of generative ai engineer openings are fully remote or hybrid as of November 2026, making it one of the more flexible engineering disciplines. Roles focused on prompt engineering, API integration, and evaluation tend to be most commonly offered remotely, while positions involving proprietary infrastructure or on-premise model deployment are more likely to require on-site presence.
How do you become a generative ai engineer?
Start by building a strong foundation in Python and machine learning fundamentals, then move into hands-on work with transformer architectures and pre-trained models through open-source projects or coursework. Practice fine-tuning models on domain-specific datasets, build at least one end-to-end application that uses a generative model in production, and document the infrastructure decisions you made along the way. Familiarity with vector databases, prompt engineering patterns, and model evaluation methods rounds out the core skill set employers look for.
Can you get a generative ai engineer job with little experience?
Yes, entry-level generative AI roles exist, and employers hiring at that level prioritize demonstrated projects over years of experience. Build a public portfolio that shows you've integrated an LLM into a real application, contributed to an open-source AI project, or fine-tuned a model on a specific dataset. Roles titled AI engineer, ML engineer, or applied AI developer often have lower experience bars and serve as strong entry points into the field.
What does the generative ai engineer interview process look like?
Most generative AI engineer interviews include a recruiter screen followed by a technical phone interview covering Python, ML concepts, and prior project experience. A take-home or live coding assessment typically tests your ability to build or evaluate a generative AI component, such as a retrieval pipeline or an evaluated prompt chain. Final rounds usually include a system design interview focused on inference infrastructure and a cross-functional conversation with product or research stakeholders about your approach to model tradeoffs and safety.
Where can I find and apply to generative ai engineer jobs?
You can find and apply to generative ai engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your experience and specialization, then apply directly to each one that fits. The platform pulls in openings from a wide range of companies, so you can compare roles across industries without searching multiple sites.
See All 184+ Generative AI Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Generative AI Engineer Jobs