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Open nowPosted 154 days ago

Backend Engineer – GenAI

Wohlig18 open roles

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Your applicationOpen nowBackend Engineer – GenAIWohlig

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The clock on this job

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Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 154 days ago

The posting

Job Overview

Architect and build scalable, high-performance backend systems while working on mission-critical platforms that process real-time market data and portfolio analytics. The role also involves leveraging Generative AI capabilities to enhance data intelligence, automation, and user-facing features, while ensuring regulatory compliance and secure financial transactions.

Key Responsibilities

  • Design, develop, and maintain scalable backend services and APIs using NodeJS and Python
  • Build event-driven architectures using RabbitMQ and Kafka for real-time data processing
  • Develop and manage data pipelines integrating PostgreSQL and BigQuery for analytics and warehousing
  • Integrate and deploy Generative AI models (LLMs, embeddings, AI APIs) into backend systems for automation, insights, and intelligent workflows
  • Design AI-powered features such as recommendation systems, document processing, or conversational interfaces
  • Ensure system reliability, security, and low-latency performance for mission-critical systems
  • Lead technical design discussions, conduct code reviews, and mentor junior engineers
  • Optimize database queries, implement caching strategies, and improve overall system performance
  • Collaborate with cross-functional teams to deliver end-to-end product features
  • Implement monitoring, logging, and observability solutions

Required Skills and Qualifications

  • 5+ years of professional backend development experience
  • Strong expertise in NodeJS and Python for production-grade applications
  • Proven experience building RESTful APIs and microservices architectures
  • Experience working with Generative AI frameworks/APIs (OpenAI, LangChain, vector databases, prompt engineering)
  • Understanding of integrating LLMs into production systems (RAG, embeddings, fine-tuning basics)
  • Strong proficiency in PostgreSQL, including query optimization and schema design
  • Hands-on experience with RabbitMQ and Kafka
  • Experience with BigQuery or similar data warehousing solutions
  • Solid understanding of distributed systems, scalability patterns, and high-traffic applications
  • Strong knowledge of authentication, authorization, and security best practices
  • Experience with Git, CI/CD pipelines, and modern development workflows
  • Excellent problem-solving and debugging skills
  • Exposure to fintech or financial services, cloud platforms (GCP/AWS/Azure), Docker/Kubernetes, caching tools (Redis/Memcached), and regulatory requirements (KYC, compliance, data privacy) is a plus.
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