Generative AI Engineer Job Description Template

Need a skilled Generative AI Engineer fast? Use our job description template to attract top talent and streamline your hiring for high-performance web apps.

Written by Antik P. — Lead Software Engineer - AI, Cloud and Generative AI Platforms · Softaims Generative AI Engineer network

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Generative AI is revolutionizing the way we interact with technology by enabling machines to create content autonomously. This cutting-edge field combines machine learning, deep neural networks, and creative thinking to produce text, images, music, and more.

The demand for generative AI developers is skyrocketing as businesses recognize the potential of AI to enhance creativity, automate processes, and provide personalized user experiences. Companies across various industries are investing heavily in AI-driven solutions.

Generative AI developers possess unique skills that blend technical expertise with creativity, allowing them to build systems that can generate novel content. This role requires a deep understanding of algorithms, neural networks, and data science.

As the field of AI continues to evolve, developers specializing in generative AI are at the forefront of technological innovation. They are tasked with creating systems that push the boundaries of what machines can achieve in terms of creativity and problem-solving.

Joining the realm of generative AI not only offers exciting challenges and opportunities for growth but also places you in a high-demand career path with the potential for substantial impact and innovation in the tech industry.

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Generative AI Engineer Job Description Template

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Job Description:

As a Mid-Level Generative AI Specialist, you will be responsible for owning and delivering medium-sized features end-to-end, focusing on the integration of generative AI capabilities into our products. You will collaborate closely with product managers, designers, and backend engineers to ensure that our AI solutions meet user needs and business objectives. Your role will involve designing, developing, and deploying AI models that enhance user experience and drive innovation within our product offerings.

Success in this role means effectively integrating AI models into production environments, optimizing performance, and ensuring scalability. You will be expected to demonstrate independence in problem-solving, make informed delivery judgments, and actively participate in code reviews and technical discussions. Your contributions will directly impact the product's functionality and user satisfaction, making you a key player in our technology team.

Tech Stack:

  • Framework/UI: Utilize React.js for building dynamic user interfaces that integrate seamlessly with AI components.
  • Language: Leverage Python for developing and training AI models, ensuring robust and efficient code.
  • State and data: Implement state management using Redux to maintain consistent data flow between AI models and UI components.
  • Styling/design system: Employ CSS-in-JS solutions like Styled Components to ensure maintainable and scalable design systems.
  • API integration: Work with RESTful APIs to connect AI models with external data sources, ensuring data integrity and availability.
  • Testing: Use Jest and Enzyme for comprehensive unit and integration testing, ensuring AI model reliability and performance.
  • Build and deployment: Automate build processes with Webpack and deploy AI solutions using Docker for consistent environments.
  • Observability: Implement monitoring with Prometheus and Grafana to track AI model performance and detect anomalies in production.
  • Collaboration/platform: Use GitHub for version control and collaborative development, ensuring seamless integration of AI features.

How We Work:

  • Squad delivery: Operate within cross-functional squads, delivering AI features in alignment with product goals and timelines.
  • Product/design/backend collaboration: Engage in regular syncs with product managers, designers, and backend teams to align on feature requirements and technical feasibility.
  • Code reviews: Participate in peer code reviews, providing constructive feedback to maintain code quality and share AI knowledge.
  • Release cadence: Follow a bi-weekly release cycle, ensuring timely delivery of AI enhancements and bug fixes.
  • Documentation: Maintain comprehensive documentation for AI models and integration processes, facilitating knowledge sharing and onboarding.
  • QA partnership: Collaborate with QA teams to define test cases and ensure AI solutions meet quality standards before deployment.
  • Production monitoring: Implement monitoring and alerting systems to proactively identify and resolve production issues in AI models.
  • Technical decision-making: Contribute to technical decision-making processes, bringing insights into AI model selection and optimization.

Job Responsibilities:

  • Design: Design generative AI models that enhance product capabilities and meet defined user requirements.
  • Develop: Develop AI algorithms and integrate them into existing systems, ensuring seamless operation.
  • Optimize: Optimize AI models for performance and scalability, reducing latency and resource consumption.
  • Test: Conduct rigorous testing of AI models to ensure accuracy and reliability in various scenarios.
  • Integrate: Integrate AI solutions with APIs, enabling data exchange and functionality across platforms.
  • Debug: Identify and resolve issues in AI models and integrations, ensuring smooth operation in production.
  • Document: Document AI model architectures and integration processes for future reference and team knowledge sharing.
  • Review: Participate in code reviews, providing feedback and ensuring adherence to coding standards.
  • Collaborate: Work closely with product and design teams to translate user needs into technical requirements.
  • Mentor: Mentor junior team members, sharing expertise in AI development and best practices.
  • Research: Stay updated with the latest advancements in generative AI and propose innovative solutions to enhance our offerings.
  • Contribute: Contribute to the continuous improvement of AI development processes and methodologies.

Required Skills:

  • Experience: 3+ years of professional experience in AI development, with at least 2 years focused on generative AI in production environments.
  • Language proficiency: Strong proficiency in Python or a similar language, with experience in AI model development and deployment.
  • Debugging: Expertise in debugging and troubleshooting AI models and integrations in production settings.
  • Testing: Experience with unit and integration testing frameworks to ensure AI model reliability.
  • Version control: Proficient in using Git for version control and collaborative development.
  • API integration: Experience integrating AI models with RESTful APIs, ensuring seamless data flow and functionality.
  • Performance awareness: Strong understanding of performance optimization techniques for AI models and systems.
  • Estimation: Ability to estimate effort and time required for AI feature development and integration.
  • Communication: Excellent communication skills, with the ability to articulate complex AI concepts to non-technical stakeholders.

Nice to Have:

  • Framework experience: Advanced experience with AI frameworks such as TensorFlow or PyTorch, enhancing model development capabilities.
  • Design systems: Familiarity with design systems and their integration into AI-driven user interfaces.
  • Visual regression: Experience with visual regression testing to ensure UI consistency when integrating AI features.
  • Accessibility: Knowledge of accessibility standards and how to implement them in AI-enhanced applications.
  • Internationalization: Experience with i18n and localization processes for AI models and applications.
  • Cloud/CDN exposure: Exposure to cloud platforms and CDNs for deploying and scaling AI solutions.
  • Regulated industry experience: Experience working in regulated industries, ensuring AI compliance with industry standards.
  • Analytics/experimentation: Experience with analytics tools and A/B testing to evaluate AI model performance and impact.

Interview Process:

  1. Initial Screening (30 minutes): A conversation with HR to discuss your background, experience, and interest in the Mid-Level Generative AI Specialist role.
  2. Technical Assessment (1 hour): A practical coding exercise focused on generative AI model development and integration, assessing problem-solving and technical skills.
  3. Technical Interview (1.5 hours): An in-depth interview with a senior engineer to discuss your technical expertise, particularly in AI model optimization and deployment.
  4. Team Collaboration Interview (1 hour): Meet with product and design team members to explore your collaboration skills and ability to translate requirements into AI solutions.
  5. Final Interview (1 hour): A discussion with the engineering manager to assess cultural fit, career goals, and alignment with company values.

Perks and Benefits:

  • Competitive compensation: Attractive salary package with performance-based bonuses and equity options.
  • Healthcare: Comprehensive health, dental, and vision insurance plans to support your well-being.
  • PTO: Generous paid time off policy, including vacation, sick leave, and holidays.
  • Learning budget: Annual budget for professional development, including courses, conferences, and certifications.
  • Remote/hybrid support: Flexible work arrangements, with options for remote or hybrid setups to suit your lifestyle.
  • Equipment: Provision of high-quality equipment and tools to ensure a productive work environment.
  • Retirement plan: 401(k) plan with company matching to help you save for the future.
  • Career progression: Clear career paths and growth opportunities within the engineering team.
  • Engineering culture: A collaborative and innovative engineering culture that values creativity and continuous improvement.

Salary Expectations:

The salary range for a Mid-Level Generative AI Specialist in 2026 is expected to be between $110,000 and $150,000 USD annually. This range may vary based on factors such as location, company size, industry, and the candidate's level of specialization and experience. Additionally, companies offering remote or hybrid work setups may provide different compensation packages to reflect the flexibility offered.

It's important to note that salary is not guaranteed and may be influenced by individual negotiation, performance-based bonuses, and equity options. Candidates are encouraged to consider the full compensation package, including benefits and growth opportunities, when evaluating job offers.

About the Author

Oleksandr K., developer
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    By Oleksandr K.

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  • Experience icon

    10 years of experience

My name is Oleksandr K. and I have over 10 years of experience in the tech industry. I specialize in the following technologies: JavaScript, Stable Diffusion, Cloud Architecture, PyTorch, TensorFlow, etc.. I hold a degree in Master of Computer Applications (MCA), . Some of the notable projects I've worked on include: Generative AI Backend for architectrender.com, Generative AI backend for Architecture redesign app, Generative AI Backend for logodiffusion.com, Stable Diffusion SAAS. I am based in Vinnitsya, Ukraine. I've successfully completed 4 projects while developing at Softaims.

My expertise lies in deeply understanding and optimizing solution performance. I have a proven ability to profile systems, analyze data access methods, and implement caching strategies that dramatically reduce latency and improve responsiveness under load. I turn slow systems into high-speed performers.

I focus on writing highly efficient, clean, and well-documented code that minimizes resource consumption without sacrificing functionality. This dedication to efficiency is how I contribute measurable value to Softaims' clients by reducing infrastructure costs and improving user satisfaction.

I approach every project with a critical eye for potential bottlenecks, proactively designing systems that are efficient from the ground up. I am committed to delivering software that sets the standard for speed and reliability.

Skills:
Previously worked at:Agile Engine

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Ivan Ž., Senior Software Engineer - AI, Machine Learning and Generative AI Platforms at Softaims

Ivan Ž.

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Gaurav K.

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Mohammad Suhel S.

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Sanjay K.

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Saqib S.

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Arsalan M., Lead Software Engineer - AI, Machine Learning and Generative AI Platforms at Softaims

Arsalan M.

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Timezone: UTC-06:00UTC-06:00
Country: United StatesUnited States
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Sandeep K.

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Timezone: UTC+05:30UTC+05:30
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Abhik M., Software Engineer - AI, Generative AI and Computer Vision Platforms at Softaims

Abhik M.

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Working with Softaims allowed us to quickly onboard highly skilled engineers who integrated seamlessly with our team. The experience was smooth and the results exceeded our expectations.

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Kirill, CT0 at EdAider
Kirill

CT0 at EdAider

The Softaims platform gave us access to developers who immediately added value. Their expertise and professionalism made the entire process seamless.

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