ABOUT THE ROLE
As an Senior AI Engineer, you’ll be designing and deploying production- grade AI systems that directly move revenue, shape product strategy, and unlock growth across Global markets. Your models should serve for billions of events, live traffic, and show up in Company- wide KPOs. Beside, from fine- tuning LLMs to crafting recommendation engines, from designing Retrieval- Augmented Generation (RAG) pipelines to launching scalable microservices, you’ll work in the core Business Enablement (BE) squad alongside Product, Tech, and Marketing in a fast- paced, Agile playground where experimentation, ownership, and impact rule the day. If you’re ready to jump into real- world AI that delivers tangible outcomes in Global eCommerce, Crossian is your start.
At Crossian, AI isn’t a buzzword, it’s our business engine. As we target from a $200M data- driven eCommerce platform toward Unicorn $1B, the Data & AI Team leads the charge by building full- stack AI solutions that power real- time recommendations, dynamic pricing, hyper- personalized storefronts, and GenAI- driven customer experiences across millions of transactions.
WHAT YOU WILL DO
Model Development & Innovation
• Build, train, and tune ML models for recommendations, propensity scoring, fraud detection, and demand forecasting.
• Prototype quickly, run offline/online experiments, and iterate based on precision, recall, CTR, and business lift.
• Fine- tune and evaluate LLMs (GPT, Llama 3, Claude, etc.) for RAG pipelines, chatbots, and content- generation features.
MLOps & Productionisation
• Implement monitoring for drift, latency, and cost, owning the full model lifecycle from commit to sunset.
• Package models into scalable micro- services with Docker/Kubernetes, SageMaker, Vertex AI, or on- prem GPU clusters.
• Automate training, CI/CD, and rollout using GitLab CI, Terraform, and blue/green or canary deployments.
Data Engineering & Feature Platforms
• Partner with Data Engineering to define feature contracts, real- time pipelines (Kafka, Kinesis), and data- quality checks.
• Design vector- database schemas (OpenSearch, Pinecone, Chroma) and retrieval logic for RAG- based solutions.
Experimentation & Evaluation
• Publish clear experiment readouts that influence product roadmaps and marketing budgets.
• Design online A/B and interleaving tests to measure incremental lift and guard- rail metrics.
Cross- Functional Collaboration & Mentorship
• Embed in product squads, translating business problems into model specs and success metrics.
• Mentor junior engineers and drive best practices in coding standards, documentation, and peer review.
