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A leading medical company based in Caesarea is seeking an AI Developer with 2+ years of software development experience to join its growing team.
Key Responsibilities:
Define and lead the vision and roadmap for AI-driven solutions.
Design, implement, and deploy AI agents as part of the development team.
Conduct research and optimize LLM outputs to improve accuracy and relevance.
Manage the full development lifecycle of AI agents, from concept to deployment and continuous improvement.
Analyze product performance based on KPIs and introduce enhancements accordingly.
Ensure adherence to responsible AI principles, including transparency, fairness, and trust.

We are looking for a highly skilled AI Engineer with a strong engineering mindset to bridge the gap between research and production.

In this role, you will be responsible for validating AI models developed by our Data Science team against real-world production systems, and then leading their optimization, deployment, and ongoing maintenance.

You will be part of the R&D team, working closely with engineers, data scientists, and product managers to ensure our AI solutions are scalable, reliable, and deliver long-term value.

If you enjoy working at the intersection of AI and engineering bringing models to life in production, optimizing for performance, and building reliable systems this role is for you!

Responsibilities
Lead the transition of AI models from proof-of-concept to full-scale production, ensuring they meet architectural, scalability, and performance standards.
Build observability and troubleshooting tools for AI services in production, including logging, performance tracking, and failure analysis pipelines.
Optimize inference performance, including latency, resource usage, and throughput, while maintaining model quality.
Manage model versioning and deployment readiness, including handoff processes, rollback plans, and configuration management.
Partner with the Data Science team to assess model readiness for production, validate input and output compatibility, and ensure assumptions align with real-world system behavior.
Collaborate cross-functionally with DevOps, backend engineers and data scientists to ensure scalable, secure, and cost-effective deployment of ML models

We are looking for a skilled DevOps Engineer to join our R&D infrastructure team and play a key role in building and scaling cloud-based platforms. In this position, you will design, implement, and maintain modern CI/CD pipelines, manage multi-cloud environments, and support microservices-based architectures. You will work closely with developers, QA, and product teams to streamline delivery processes, improve system reliability, and ensure smooth deployments. This is a hands-on role where you will directly influence the stability, scalability, and efficiency of our production systems while leveraging cutting-edge technologies across AWS and Azure.

Responsibilities
Infrastructure as Code (IaC): Develop and maintain infrastructure using tools like Terraform, Ansible
Cloud Infrastructure Management: Deploy, manage, and monitor applications in cloud environments(aws and Azure)
Collaboration & Support: Work closely with developers, QA, and product teams to streamline releases and improve productivity.
Provide technical support for development and operations teams during incidents and deployments.
CI/CD Pipeline Management:
Design, implement, and maintain continuous integration and delivery pipelines. Automate build, test, and deployment processes to improve speed and reliability.

We are looking for a forward-thinking Data Scientist with a passion for Generative AI (GenAI) and emerging AI technologies. This role is ideal for those who thrive in rapid prototyping, proof-of-concept (PoC) development, and iterative experimentation. You will work across multiple projects, transforming innovative ideas into practical AI solutions while engaging with clients for feedback and improvement.

Responsibilities
Generative AI Innovation & Research: Design PoCs with LLMs, RAG, RL, and agent-based AI. Apply emerging AI methods to real-world business needs.
Prototyping & Implementation: Translate research into scalable prototypes and production solutions. Ensure models are efficient, adaptable, and enterprise-ready. Lead integration, A/B testing, and phased rollouts.
AI Engineering & Deployment: Architect scalable GenAI solutions for banking. Own the full lifecycle: deployment, monitoring, incident response. Build dashboards, detect model drift, and integrate feedback loops.

Join us as a Senior DevOps Engineer and shape our cloud infrastructure strategy as we scale. You'll lead critical initiatives across our development lifecycle while working with cutting-edge technologies in a collaborative, growth-focused environment.
You will:
Design and implement cloud infrastructure across development, testing, and production environments on AWS.
Ensure our production environment maintains the highest standards of stability, availability, and performance.
Review the current automation strategy partnering with stakeholders to implement a holistic, scalable solution that supports our multi-year growth trajectory
Work with the Information Security team to improve security, enhance data isolation, access controls and network/application security across our infrastructure.