Delty
About Us
Delty is building the healthcare’s AI operating system . We create voice-based and computer-based assistants that streamline clinical workflows, reduce administrative burden, and help providers focus on patient care. Our system learns from real healthcare environments to deliver reliable, context-aware support that improves efficiency and elevates the provider experience.
Delty was founded by former engineering leaders from
Google, including co-founders with deep experience at YouTube and in large-scale infrastructure . You’ll get to work alongside people who built massive systems at scale — a chance to learn a lot and contribute meaningfully from day one.
We believe in solving hard problems together as a team, iterating quickly, and building software with long-term thinking and ownership.
What You’ll Do
Work full-stack : design and build features spanning front-end, back-end, data storage and processing.
Build new product modules and services from scratch
— or evolve existing ones — guided by context-aware system design.
Work with AI and machine learning : integrate large-language models (LLMs), process large or long-form text data, apply traditional ML (e.g. regression, data pipelines), and build tooling around AI-driven flows.
Make architectural decisions —
choose frameworks, data models, APIs, storage solutions — balancing trade-offs between performance, scalability, maintainability, and complexity.
Collaborate closely with co-founders
and other engineers to translate product vision into a working, maintainable codebase.
What We’re Looking For
At least 3 years of full-stack engineering experience , including substantial work with AI/ML.
Strong skills across front-end, back-end, databases/data storage
— and demonstrated ability to design end-to-end systems.
Experience working with or integrating AI/ML
— LLMs, data pipelines, long-form text processing, traditional ML like regression or statistical modeling.
Good design sense and architectural thinking : you understand trade-offs (scalability vs complexity, speed vs maintainability) and can choose wisely based on constraints.
Comfort working in a fast-paced startup-style environment : nimble, iterative, high ownership.
Bonus: prior startup experience, or even having been a founder
— we value entrepreneurial thinking, self-direction, and willingness to wear multiple hats.
Why join
Learn from seasoned Google engineers : As former Google engineers who built systems at YouTube and Google Pay, we’ve operated at massive scale. Working alongside us gives you a chance to build similar systems and learn best practices, scale thinking, and software design deeply.
High impact : At a small but ambitious team, your contributions will influence architecture, product direction, and core features. You will have real ownership and see the effects of your work quickly.
Grow fast : We’re iterating rapidly; you’ll be exposed to the full stack, AI/ML pipelines, system architecture, data modeling, and product-level decisions — a fast-track to becoming a senior engineer or technical lead.
Challenging and meaningful work : We’re tackling the hardest part of software engineering: bridging AI-generated prototypes and robust, scalable enterprise-grade systems. If you enjoy thinking deeply about systems and building reliable, maintainable foundations — this is for you.
#J-18808-Ljbffr
Delty was founded by former engineering leaders from
Google, including co-founders with deep experience at YouTube and in large-scale infrastructure . You’ll get to work alongside people who built massive systems at scale — a chance to learn a lot and contribute meaningfully from day one.
We believe in solving hard problems together as a team, iterating quickly, and building software with long-term thinking and ownership.
What You’ll Do
Work full-stack : design and build features spanning front-end, back-end, data storage and processing.
Build new product modules and services from scratch
— or evolve existing ones — guided by context-aware system design.
Work with AI and machine learning : integrate large-language models (LLMs), process large or long-form text data, apply traditional ML (e.g. regression, data pipelines), and build tooling around AI-driven flows.
Make architectural decisions —
choose frameworks, data models, APIs, storage solutions — balancing trade-offs between performance, scalability, maintainability, and complexity.
Collaborate closely with co-founders
and other engineers to translate product vision into a working, maintainable codebase.
What We’re Looking For
At least 3 years of full-stack engineering experience , including substantial work with AI/ML.
Strong skills across front-end, back-end, databases/data storage
— and demonstrated ability to design end-to-end systems.
Experience working with or integrating AI/ML
— LLMs, data pipelines, long-form text processing, traditional ML like regression or statistical modeling.
Good design sense and architectural thinking : you understand trade-offs (scalability vs complexity, speed vs maintainability) and can choose wisely based on constraints.
Comfort working in a fast-paced startup-style environment : nimble, iterative, high ownership.
Bonus: prior startup experience, or even having been a founder
— we value entrepreneurial thinking, self-direction, and willingness to wear multiple hats.
Why join
Learn from seasoned Google engineers : As former Google engineers who built systems at YouTube and Google Pay, we’ve operated at massive scale. Working alongside us gives you a chance to build similar systems and learn best practices, scale thinking, and software design deeply.
High impact : At a small but ambitious team, your contributions will influence architecture, product direction, and core features. You will have real ownership and see the effects of your work quickly.
Grow fast : We’re iterating rapidly; you’ll be exposed to the full stack, AI/ML pipelines, system architecture, data modeling, and product-level decisions — a fast-track to becoming a senior engineer or technical lead.
Challenging and meaningful work : We’re tackling the hardest part of software engineering: bridging AI-generated prototypes and robust, scalable enterprise-grade systems. If you enjoy thinking deeply about systems and building reliable, maintainable foundations — this is for you.
#J-18808-Ljbffr