Note: The job is a remote job and is open to candidates in USA. Petco is a pet care company serving pets and pet parents through products, services, stores, veterinary hospitals, and preventive care clinics. The Sr. Engineer, AI Platform Engineering will design, architect, and deploy scalable AI infrastructure, foundation models, and generative AI solutions, while establishing MLOps and LLMOps capabilities and collaborating with software, product, data, and business teams.
Responsibilities
- Lead end-to-end AI architecture and solution design to build resilient, enterprise-grade platform infrastructure
- Design and implement Generative AI capabilities, including LLMs, foundation models, RAG (Retrieval-Augmented Generation), and Agentic AI / AI agents
- Architect efficient model serving and high-throughput inference systems optimized for real-time and batch workloads
- Integrate embeddings, vector databases, and cloud AI/ML services into core engineering products
- Establish and champion MLOps and LLMOps best practices across the engineering organization
- Build automated CI/CD pipelines specifically tailored for AI/ML applications, ensuring seamless testing, deployment, evaluation, and monitoring
- Design end-to-end AI platform pipelines emphasizing scalability, security, high availability, and performance
- Stay at the forefront of artificial intelligence technologies, open-source foundation models, and emerging platform tooling
- Lead evaluation and proof-of-concept initiatives for cutting-edge generative AI frameworks, inference engines, and vector stores
- Partner with software engineers, system architects, and business stakeholders to drive seamless AI application integration into production ecosystems
- Translate complex enterprise requirements into robust, reusable AI platform services and developer APIs
- Provide technical leadership, architectural guidance, and mentorship to software and platform engineers
- Maintain comprehensive documentation of AI architectures, platform interfaces, design patterns, and operational procedures
- Foster a culture of technical excellence and contribute to internal technical knowledge repositories
- Continuously evaluate and optimize AI platform infrastructure, runtime performance, resource utilization, and reliability
Skills
- Bachelor's, Master's, or Ph.D. in Computer Science, Software Engineering, or a related technical field
- 5+ years of hands-on experience in software engineering, platform engineering, or AI engineering in production environments
- Proven track record in end-to-end AI solution design, model serving, inference optimization, and AI application integration
- Strong expertise with Generative AI concepts including LLMs, foundation models, RAG architectures, embeddings, and vector databases
- Hands-on experience implementing MLOps / LLMOps frameworks and building robust CI/CD pipelines for AI/ML applications
- Advanced programming proficiency in languages such as Python, Go, or Java
- Demonstrated technical leadership and mentorship capabilities
- Excellent problem-solving, architectural design, and communication skills
- Deep hands-on experience with major cloud platforms and cloud AI/ML services (e.g., AWS, Azure, Google Cloud)
- Strong familiarity with containerization, microservices, and orchestration tools (e.g., Docker, Kubernetes, Ray)
- Experience with distributed systems and big data technologies
- Strong foundation in modern software development methodologies, API design, and system reliability engineering (SRE)
Benefits
- Health and financial benefits
- 401K
- Incentives
- PTO
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