Solutions Architect

5 days ago

madurai, India beBeeBackend Full time

Job Description:As a Founding Backend Engineer, you will play a critical role in architecting the nervous system of our AI Operator.The core decision engine relies on a perfect understanding of reality to make high-stakes financial trades. Your job is to build the Context Layer which serves as the sensory system that determines how our system sees the world.You will own the infrastructure that fuses rigid financial data with messy and unstructured signals. You will architect the universal data model that standardizes chaotic inputs from ad platforms, MMPs, first-party data and our own internal actions into a single unified language for our models.We are looking for someone who can design and maintain canonical data models that normalize conflicting metrics across disparate sources. This includes mapping data from ad platforms like Meta and Google, MMPs like AppsFlyer, first-party data and our own internal actions and observers into a single unified language for our models.Responsibilities include designing pipelines to ingest high-fidelity signals directly from the source, constructing workflows that scrape and process multimodal data from ad libraries and social platforms, and building the logging and observation infrastructure that records every state change.Requirements:Experience building high-throughput backend systems in Python, Go or Java.Understanding of data polyglots, including SQL, NoSQL and message queues.Ability to handle data that arrives in different shapes, sizes and speeds.Able to challenge assumptions and dig in until finding the root cause.Benefits:Salary: $170,000 – $220,000.Significant equity package commensurate with a founding role.Daily lunch and dinner.Relocation support for candidates moving to the Bay Area.Comprehensive health, dental, vision and unlimited PTO.Bonus Points:Experience building low-latency systems such as high-frequency trading platforms, gaming backends or real-time bidding exchanges.Complex scraping experience, gathering data from difficult sources where APIs do not exist or are rate-limited.Familiarity with event-driven architectures (Kafka, RabbitMQ) and managing concurrency in a high-volume environment.Experience managing ETL pipelines for terabyte-scale datasets using tools like Airflow, dbt or Spark.Compensation & Benefits],

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