eBay
Full Stack Engineer MTS 2 – AIRI
RemoteUnited States only
- Role
- Fullstack
- Experience
- Lead
- Employment
- Full-time
- Company size
- Enterprise
Salary not disclosed
Check eligibility
Open to US only. Set where you work from to check your eligibility.
No BS summary
Senior Full Stack Engineer (MTS 2) for AI Research and Innovation division. Requires 8+ years of software/ML/AI engineering experience, with 4+ years in production AI/ML systems. Must have strong backend depth, architectural judgment, and a full-stack mindset. Experience with Generative AI, LLMs, and agent-based systems is essential. Will lead technical execution, mentor engineers, and work across the full AI lifecycle.
Core skills
Generative AILLMsagent-based architectures
Required skills
JavaPythonPyTorchTransformersscikit-learnSpring FrameworkSpring BootDockerKubernetesHadoopSparkCI/CD
Optional skills
C++CUDAKafkaFlinkBeamStormvector databasesembeddings
What you'll do
- Design, develop, and optimize scalable AI systems using Generative AI, LLMs, retrieval-augmented generation, and agent-based architectures.
- Lead technical execution for major AI workstreams, services, or platform components from design through production deployment.
- Build agent-led user experiences and backend systems that leverage task decomposition, memory, tool use, planning, retrieval, and orchestration.
- Partner with Product, Research, Data Engineering, and Software Engineering teams to translate business and user needs into practical AI system designs.
- Own architectural decisions for assigned systems or subsystems, ensuring reliability, maintainability, scalability, cost efficiency, and production readiness.
- Contribute directly to implementation across backend services, model integration layers, APIs, orchestration services, evaluation pipelines, and observability tooling.
- Lead and participate in design reviews, code reviews, technical planning discussions, and operational readiness reviews.
- Help advance eBay’s internal GenAI platform through reusable components, APIs, frameworks, evaluation patterns, and engineering guidelines.
- Define and implement approaches for AI system evaluation, including quality measurement, experimentation, regression testing, model behavior analysis, and production feedback loops.
- Monitor and optimize AI systems in production for latency, quality, scalability, reliability, cost, and responsible AI use.
- Break down ambiguous technical problems into clear implementation plans, milestones, risks, and tradeoffs.
- Mentor engineers through hands-on technical guidance, implementation support, code reviews, and collaborative problem-solving.
- Stay current on advances in LLMs, AI agents, retrieval systems, machine learning infrastructure, and emerging AI tooling, applying a practical lens to production use.
- Contribute to continuous improvement across design, implementation, deployment, monitoring, and operational processes.
What they require
- 8+ years of experience in software engineering, machine learning engineering, AI engineering, or related technical roles.
- 4+ years of focused experience developing, deploying, and operating AI-centric or ML-powered systems in production environments.
- 1–2+ years of experience leading technical initiatives, owning major engineering workstreams, mentoring engineers, or providing technical direction.
- Hands-on experience building Generative AI, LLM, retrieval-augmented generation, conversational AI, or agent-led systems.
- Experience taking AI-powered features or services from prototype to production with attention to maintainability, scalability, performance, reliability, and user impact.
- Strong hands-on engineering skills, with the ability to contribute directly to complex system design and implementation.
- Strong programming skills in Java or similar JVM languages, with working proficiency in Python and familiarity with ML frameworks such as PyTorch, Transformers, and scikit-learn.
- Experience designing and operating production-grade backend systems, distributed services, APIs, or AI platforms that serve real-world user traffic.
- Full-stack mindset with the ability or willingness to contribute to front-end development using modern web technologies; expertise in a specific front-end framework is not required.
- Strong understanding of AI system evaluation, including offline evaluation, online experimentation, model behavior analysis, quality metrics, and feedback loops.
- Hands-on experience with: Spring Framework or Spring Boot Docker and Kubernetes Large-scale data technologies such as Hadoop or Spark Distributed systems and scalable backend services Production monitoring, observability, and performance optimization CI/CD, testing, deployment, and operational support practices
- Ability to evaluate technical tradeoffs and communicate complex AI concepts clearly to technical and non-technical collaborators.
Benefits
- eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, and disability, or other legally protected status.
- If you have a need that requires accommodation, please contact us at talent@ebay.com . We will make every effort to respond to your request for accommodation as soon as possible.
- View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility.
- We use cookies to enhance your experience and may use AI tools for administrative tasks in the hiring process.
- To learn how we handle your personal data and use AI responsibly, please visit our Talent Privacy Notice , Privacy Center , and AI Hiring Guidelines .
American multinational internet corporation that manages eBay.com
Salary not disclosed