Tech Stack
AWSGoKafkaPostgresPyTorchReactSparkTensorflowTerraformTypeScript
About the role
- Redefine customer engagement for e-commerce brands by building AI-powered ambassadors for Email and SMS
- Refine AI infrastructure for deeper segmentation, richer customer-level memory, and advanced agentic workflows
- Enhance conversation engine to deliver self-optimizing dialogues that surface actionable feedback
- Expand self-service capabilities so brands of all sizes can access LTV.ai friction-free
- Build and optimize data pipelines capable of processing millions of events daily and supporting multi-LLM orchestration
- Write and review production code, collaborate across engineering and product teams, and ship fast
Requirements
- 5+ years engineering experience, with 3+ years building production-scale ML systems (recommendations, ranking, or personalization)
- Proven track record of optimizing data pipelines and real-time services for tens of millions of monthly users
- Proven experience deploying LLM‑powered products at scale: fine‑tuning or prompt‑engineering models, implementing retrieval‑augmented generation, evaluating quality, and optimizing latency/cost across tens of millions of monthly users.
- Deep expertise in modern ML frameworks (PyTorch, TensorFlow, or JAX)
- Strong backend chops in TypeScript/NestJS, Go, or equivalent
- Hands-on experience with distributed data processing (Kafka, Spark, Flink) and columnar stores such as ClickHouse
- Solid grasp of AWS services (EKS, S3, Lambda, SageMaker) and infrastructure as code (Terraform)
- Familiarity with AI coding accelerators (Cursor, Windsurf, Copilot, etc.)
- Passion for shipping fast—you’ll spend the majority of your time writing and reviewing production code