לוח משרות דרושים עבודה היברידית

Your Impact:
Lead the full product lifecycle for web and cloud-based products and features, from initial concept and product requirements definition through execution and successful adoption.
Engage daily with sales and Fortune 500-class clients to proactively gather user needs, feedback, and market intelligence, and translate these insights into solutions that address their problems.
Collaborate closely with UX, engineering, sales, and customer success teams to develop and deliver high-quality, impactful products.
Analyze feature performance metrics and strategically iterate until key business objectives are met customer satisfaction is achieved.
Contribute to shaping and defining a new product category within the software development toolkit domain.

Our offices are located in Tel Aviv, near the Hashalom train station and the Yehudit light rail station, with on-site parking available. We offer a hybrid work model with flexible working hours.

we are looking for a AI Security Engineer.
As AI capabilities accelerate across the bank, we need an engineer to design and enforce safe AI usage-protecting customer data, preserving model integrity, and meeting our regulatory obligations. You'll be the architect of guardrails, tooling, and policies that make AI both secure and useful for product and internal teams. This isn't about slowing things down; it's about building the trust layer that lets innovation move fast without breaking things.
What Youll Actually Be Doing:
Design enterprise AI guardrails across Azure and AWS (e.g., Azure AI Studio/Azure OpenAI, Amazon Bedrock/SageMaker): content filtering, PII redaction, prompt/response validation, and policy enforcement services.
Implement data minimization controls for GenAI/RAG workloads: context filtering, least‐privileged retrieval, document-level ACL enforcement, vector store hardening, and secure token/secret handling.
Threat model AI systems (apps, agents, RAG, fine-tuning pipelines) using frameworks like STRIDE and the OWASP Top 10 for LLM Apps; define misuse scenarios (prompt injection/jailbreaks/data exfiltration) and build mitigations.
Build monitoring and telemetry: privacy-preserving prompt/response logging, sensitive-data detection, safety/eval dashboards, drift/abuse signals, and incident hooks into our SIEM.
Integrate AI security into the SDLC: reusable libraries, pre-commit checks, CI/CD gates, policy-as-code, and secure-by-default reference architectures for product teams.
Evaluate third‑party AI vendors and internal apps: security reviews, data residency and retention requirements, SSO/SCIM integrations, DPA/TPRM inputs, and continuous control testing.
Partner across Security, Data, Privacy, and Engineering to map AI controls to FFIEC, SOC 2, and PCI DSS; document control evidence for audits.
Lead/participate in AI red‑teaming: automated jailbreak/prompt‑injection tests, safety benchmarks, purple‑team exercises, and response playbooks for AI incidents.
Enable the org with concise guidelines, examples, and training on safe AI development and usage.

we are looking for a Mid-Level, Security Engineer.
This role focuses on ensuring the security and compliance of cloud infrastructure by implementing and maintaining robust security controls across AWS environments. The position involves automation for security monitoring, adhering to best practices, and collaborating cross-functionally with other teams.
What Youll Actually Be Doing:
Cloud Security Implementation: Contribute to the design and implementation of security measures across AWS environments to ensure systems are secure, compliant, and aligned with industry best practices. Including implementation, automation and development of security policies
Conduct regular security assessments, control testing, and audits to proactively identify risks and vulnerabilities (and support remediation efforts with partner teams)
Collaboration with Internal Teams: Work closely with internal teams to integrate security best practices into development and operational workflows
Security Automation & Infrastructure Management: Design and implement automation strategies for security monitoring, auditing, and incident response
Cost Efficiency through Security: Contribute to cloud cost management by optimizing cloud resources without compromising on security.
Incident Response & Threat Management: Participate in incident response efforts to support timely identification, analysis, containment, and remediation of security threats. Contribute to post-incident reviews, help maintain incident response playbooks, and support internal teams by sharing learnings and updated procedures.

we are looking for a Security Engineering Operations Coordinator.
As the Security Engineering Operations Assistant, you'll be the organizational backbone for the VP, Security Engineering-ensuring requests move forward, deadlines stay visible, and nothing gets lost in the shuffle. This isn't about being an admin; it's about being the force multiplier that lets security leadership focus on strategy and technical priorities while you keep the machine running smoothly.
If you're the person who naturally keeps lists, follows up before being asked, and gets satisfaction from bringing order to chaos-this role was made for you.

A passionate and experienced team leader eager to lead a global multidisciplinary team, which includes front-end/full-stack developers and a QA Automation engineer. You excel in a hands-on leadership role, driving technical excellence while fostering a culture based on trust, collaboration, and professional growth. You are invigorated by technology, innovation, and creating products that significantly impact the world.

If you want to play a key role in the team and bring a real impact to the world - we are the right place for you.

Your Impact:
Lead, coach, and grow a global multidisciplinary team, fostering a culture of high performance, continuous learning, and collaboration.
Own the architectural vision and technical roadmap.
Plan and execute complex software delivery cycles from ideation to production.
Partner closely with Product Managers and stakeholders to define requirements, prioritize tasks, and translate business needs into technical solutions.
Oversee the health and performance of the application, promoting a strong "quality-first" culture.
Lead by example by remaining technically involved (hands-on) in complex features and critical code reviews.

Our offices are located in Tel Aviv, near the Hashalom train station and the Yehudit light rail station, with on-site parking available. We offer a hybrid work model with flexible working hours.

We are seeking an experienced Backend Engineer to join Evinced and play a key role in evolving our GenAI-driven products that expose and deliver our capabilities to customers.

In this role, you will design, implement, and maintain high-quality backend services that power AI-based interfaces such as MCP, Slack/VS Code chatbots, agents, and additional automation tools, ensuring seamless access to our tools and features.

You will be responsible for building reliable and scalable systems that enable developers and accessibility experts to easily leverage our technology and gain actionable insights for improving the accessibility of their code.

Your Impact:
Research and implement industry-leading technologies into our technology stack.
Design and implement scalable solutions to enhance the product architecture.
Plan and execute complex, distributed, large-scale software delivery systems.
Monitor and optimize all aspects of product performance.
Troubleshoot issues across various services and functional areas.

Our offices are located in Tel Aviv, near the Hashalom train station and the Yehudit light rail station, with on-site parking available. We offer a hybrid work model with flexible working hours.

We are seeking an experienced and visionary Data Scientist to join our dynamic technology organization. The successful candidate will be a part of a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, and a passion for continuous learning and development.
Responsibilities:
Gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) are used to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs), to create innovative solutions for our products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization. Design, implement, and optimize classic machine learning models to solve complex business problems.

We are looking for a .NET developer to join our fast-growing Acquiring dev team. You will report to the ACQ Integration Team Leader and play a key role in enhancing the Acquiring system by developing innovative new features, contributing to our teams ongoing success and growth.
Responsibilities:
Participate in all aspects of software development, including designing, hands-on coding, implementing, debugging, deployment, and troubleshooting
Accountable for overseeing the complete lifecycle of new product features and components from inception to deployment
Provide mentorship for other team members
Conduct code reviews
Be a source of knowledge for the team members regarding the technical and business aspects of the daily work
Assist the team leader in any way that is required, including leading feature development and providing guidance for other team members
Define and enforce coding standards.

Required QA Automation Engineer
Your Mission:
The QA Automation Engineer will help to continuously improve the quality, reliability and end-user experience of various solutions delivered by our development team. Also, you will help efficiently deliver high-quality solutions to end users through the use of modern quality methodologies and test automation technologies combined with a streamlined release process. The individual must be forward-thinking and share in a common vision of quality, integrity and efficiency.
Responsibilities:
Define, write, maintain & perform manual & automated tests of multiple APIs, UIs & Web services for functionality, correctness and reliability
Maintain, expand and create automation solutions
Create, maintain and execute test, bug, story & other sprint board items in Azure DevOps
Analyze and understand functional and technical requirements to devise Test cases/Test scenarios that fully meets the testing scope to satisfy business/user/system requirements
Ensure prerequisites for testing are fully prepared, test data and test environment setup/configurations
Identify and log bugs during the Software Development life cycle till release to Production
Perform root cause analysis of the bugs and collaborate with the development team to resolve and test them
Work closely with the Support team to investigate and test customer and/or production issues.
Work with your lead on improving QA processes and practices and adhering to them to ensure that quality assurance standards are met.

We are looking for a Product Data Director to lead our global product data strategy and governance. In this role, you will own the vision, implementation, and continuous improvement of how data is captured, structured, and leveraged across our product ecosystem. Youll partner closely with Product, Engineering, BI, and Operations teams to ensure data excellence, enable data-driven decision-making, and unlock insights that enhance our products, customer experience, and business growth.
Responsibilities:
Develop and execute a comprehensive product data strategy aligned with our business goals.
Define and own data standards, taxonomy, and governance frameworks across all product lines.
Partner with Product, BI, and Engineering to design scalable data models and infrastructure supporting product analytics, reporting, and performance tracking.
Lead a cross-functional data excellence initiative, ensuring high-quality, accurate, and consistent data.
Work with product managers to embed data-driven decision-making in product planning, experimentation, and optimization processes.
Oversee the implementation of data instrumentation and tracking for new product launches.
Collaborate with the Analytics and Data Engineering teams to ensure data availability and reliability across systems.

We are always looking for exceptional talent to join us on the journey!
Your Mission:
As an MLOps Engineer, your mission is to design, build, and operate the platforms that power our machine learning and generative AI products spanning real-time use cases such as large-scale fraud scoring, MCP & agentic workflows support. Youll create reliable CI/CD for models and Agents, robust data/feature pipelines, secure model serving, and comprehensive observability. You will also support our agentic AI ecosystem and Model Context Protocol (MCP) services so that models can safely use tools, data, and actions across.
You will partner closely with Data Scientists, Data/Platform Engineers, Product, and SRE to ensure every model from classic ML to LLM/RAG agents moves from prototype to production with strong reliability, governance, cost efficiency, and measurable business impact.
Responsibilities:
Operate & Develop ML/LLM platforms on Kubernetes + cloud (Azure; AWS/GCP ok) with Docker, Terraform, and other relevant tools
Manage object storage, GPUs, and autoscaling for training & low-latency model serving
Manage cloud environment, networking, service mesh, secrets, and policies to meet PCI-DSS and data-residency requirements
Build end-to-end CI/CD for models/agents/MCP tooling (versioning, tests, approvals)
Deliver real-time fraud/risk scoring & agent signals under strict latency SLOs.
Maintain MCP servers/clients: tool/resource definitions, versioning, quotas, isolation, access controls
Integrate agents with microservices, event streams, and rule engines; provide SLAs, tracing, and on-call runbooks
Measure operational metrics of ML/LLM (latency, throughput, cost, tokens, tool success, safety events)
Enforce governance: RBAC/ABAC, row-level security, encryption, PII/secrets management, audit trails.
Partner with DS on packaging (wheels/conda/containers), feature contracts, and reproducible experiments.
lead incident response and post-mortems.
Drive FinOps: right-sizing, GPU utilization, batching/caching, budget alerts.

We are seeking an experienced and visionary Data Science Team Lead to join our dynamic technology organization. The successful candidate will lead a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, exceptional leadership skills, and a passion for continuous learning and development.
Responsibilities:
Lead, mentor, and develop a team of data scientists both methodologically and technically to deliver high-impact projects aligned with our business objectives.
Design, implement, and optimize classic machine learning models to solve complex business problems.
Apply gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs) to create innovative solutions for our products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization.