4 дня назад
Engineering Leader (AI)
170 000 - 220 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Engineering Leader (AI): Building and operating DataVisor’s real-time machine learning platform for fraud detection with an accent on streaming systems, storage layers, training pipelines, and AI-assisted engineering tools. Focus on designing distributed systems, improving operational reliability, mentoring engineers, and validating LLM- and agent-generated outputs in production.
Location: Mountain View, California, United States; Workplace: Hybrid
Base salary: $170,000–$220,000 per year, commensurate with experience.
Company
provides an AI-powered fraud and risk platform with real-time fraud detection, anti-money laundering, machine learning, device intelligence, and investigation capabilities.
What you will do
- Own the technical direction of the real-time detection platform, including streaming, storage, and machine learning training pipelines.
- Translate product and engineering roadmaps into technical plans, milestones, and execution priorities.
- Lead architecture reviews, make technical trade-off decisions, and document key decisions.
- Stay hands-on with coding, code reviews, debugging, and production incident support.
- Mentor engineers and improve system design, code quality, operational excellence, and technical execution.
- Define standards for AI-assisted engineering and build tools for triage, root-cause analysis, alert summarization, and evaluation.
Requirements
- 8+ years of software development experience and 2+ years of technical leadership experience.
- Production expertise with Java and working proficiency in Python and Shell scripting.
- Experience designing, building, shipping, and operating distributed real-time systems at scale.
- Strong knowledge of computer systems, relational databases, SQL, multithreading, and concurrency.
- Hands-on experience with Cassandra, Yugabyte, Flink, Spark, or Kafka, plus experience with the Spring Framework.
- Bachelor’s degree in Computer Science or a related field is required.
Nice to have
- Experience in fraud, risk, payments, financial services, or other high-impact domains.
- Experience owning machine learning platforms or large-scale training pipelines.
- Experience with Kubernetes, LLM APIs, agent frameworks, tool calling, RAG, or MCP.
- Experience writing evaluations for non-deterministic systems, hiring or mentoring engineers, and test-driven development.
Culture & Benefits
- Open, positive, collaborative, and results-driven working environment.
- Health insurance and 401(k).
- Paid time off.
- Equity.
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