Candidates for this position are preferred to be based in Bangalore, India and will be expected to comply with their team's hybrid work schedule requirements.

What Youll do :

- Drive and own the delivery of AI platforms from design and architecture to production.

- Leverage your deep knowledge of AI engineering to build Wayfair's next generation AI capabilities.

- Design scalable systems using Python, Go, Kubernetes, GCP, Airflow, and other technologies to support AI workloads.

- Think outside of the current technology/stack limitations to push the boundaries on what is possible with AI and deliver feasible solutions collaboratively.

- Champion open source solutions and Google Cloud native technologies, and their application to our AI use cases.

- Develop end to end AI solutions that can power the full range of AI initiatives at Wayfair.

- Partner with product leaders to understand technical pain points for data scientists and other teams building AI applications and translate them into clear and robust platform solutions.

- Advise engineering and product management on AI platform technical roadmap, ensuring that the vision aligns with broader company objectives.

- Promote a culture of engineering excellence and strengthen the technical expertise of our AI engineering and product teams.

- Keep current on AI engineering technology trends, evaluate, work on proof-of-concept and make recommendations on the technologies based on their merit.

Who you are :

- 6+ years of experience in software engineering and designing systems at scale.

- 2+ years of experience in Linux-based development, Python/Go development, and leading engineering teams.

- Experience developing AI/ML pipelines, model deployment systems, and orchestrating AI workloads with Kubernetes.

- Strong understanding of containerization, AI system scalability challenges, and software engineering best practices.

- Experience with AI/ML frameworks (TensorFlow, PyTorch) and model serving technologies.

- Knowledge of AI system monitoring, performance optimization, and model lifecycle management.

- Excellent communication skills with demonstrated experience driving teams and influencing technical decisions aligned with company AI strategy.

- Hands-on experience in high-growth environments at scale, with ability to mentor engineers and collaborate with AI researchers and data scientists.

Nice to Have :

- Mix of start-up and large-company experience working on AI solutions.

- Familiarity with AI platforms (opensource or offered by Google Cloud) and how to implement them on a large scale.

- Knowledge of vector databases, embedding systems, or real-time AI inference optimization.