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Senior AI Software Engineer at QPOINT Technologies · Trevo
Company Description
QPoint Technologies is part of QPoint Group, a premier technology collective that unites the expertise of QPoint Technologies, Sensecom, and Aginix to deliver end-to-end technology solutions. With more than 250 technology professionals and consultants, the group supports complex organizations by enhancing growth, security, and operational efficiency across the full technology lifecycle.
QPoint Technologies specializes in software engineering, quality assurance, automation, and advanced technology solutions, working with leading organizations across Israel’s finance, insurance, defense, and public sectors. Since 2021, QPoint Technologies has been part of HUB Security Group (HUB.TA), a publicly traded company formed through the merger of ALD Advanced Logistics Developments Ltd. and cybersecurity firm HUB Security Ltd.
Role Description
We are looking for a Senior AI Engineer to join an innovative AI Center of Excellence and play a key role in designing, building, and scaling advanced AI-driven solutions in complex enterprise environments.
The role combines hands-on software engineering, AI/GenAI, cloud infrastructure, and system architecture, with a strong focus on building production-grade solutions powered by LLMs and agentic workflows.
Day-to-day responsibilities include designing and developing end-to-end AI/GenAI systems, from prototyping through production, using LLMs and agent frameworks such as LangGraph. The engineer will build scalable backend services, data and inference pipelines, RAG and embedding architectures, and cloud-native systems designed for high availability and scale.
The role will also involve designing distributed microservices and event-driven architectures, implementing observability and AI SDLC practices, and integrating security, governance, and compliance capabilities into AI solutions.
The ideal candidate will be highly hands-on, technically curious, and comfortable working on complex systems where software engineering, cloud infrastructure, and emerging AI technologies come together.
8+ years of experience in software development in production environments – required.
5+ years of strong hands-on experience with Python and JavaScript/TypeScript, including technologies and concepts such as asyncio, concurrency, and Pydantic – required.
3+ years of hands-on experience with AWS and cloud-native architectures, including Docker, Kubernetes, S3, Lambda, CI/CD, Observability, and managed messaging or data-streaming platforms such as AWS SQS or Kafka – required.
4+ years of experience designing scalable Microservices, event-driven architectures, and distributed backend systems, including solutions for high-load environments, traffic spikes, failure scenarios, rate limiting, queues, backpressure, and DLQs – required.
Strong understanding of software engineering principles, distributed systems, scalability, reliability, and production-grade development.
Excellent problem-solving and technical communication skills, with the ability to collaborate effectively across multidisciplinary teams.
Nice to have
Experience designing and deploying REST and/or GraphQL APIs, with knowledge of enterprise authentication and authorization technologies such as OAuth 2.0, JWT, and OIDC – a significant
Proven experience building and operating complex LLM-based solutions in production, including handling non-deterministic AI outputs at scale – a significant
Experience with AI evaluation and monitoring, including approaches such as LLM-as-a-Judge – a significant
Familiarity with MCP, A2A protocols, and agentic architectures – a significant