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The Director of Engineering - Performance Management at our company is responsible for leading and
managing the engineering teams that design, build, and maintain the companys PM product. This role ensures the delivery of high-quality, scalable, and reliable solution
that support our companys customers
How will you make an impact?
Lead the PM engineering organization, ensuring alignment with company
goals
Oversee the design, development, testing, and deployment of PM
micro services
Manage resource planning, delivery milestones, and overall product quality
Ensure system capacity planning and operational support for the PM
Establish and enforce development standards, tools, and methodologies
Integrate customer and business requirements into engineering efforts
Stay current with AI and Agentic technologies such as reasoning models, LLM, SLM, AI SDLC, Agentic coding and agents orchestration
Manage global distributed team across multiple sites
Recruit, develop, and retain top engineering talent.

Accountable for developing and implementing plans to effectively demonstrate and communicate the clinical and economic value of products to internal and external customers.

Acting as a functional leader for market access activities that include, but are not limited to, assessing market access needs/trends, and developing and executing required market access strategies to optimize market access, adoption, and commercial success.

Contributing to annual brand planning by providing robust analysis and a strong payer value proposition and to forecasting, business planning, pricing, and budgeting processes

Create and develop quantitative business cases to support contracting efforts.

Key Responsibilities:

Strategy Development:

Develop and implement comprehensive market access strategies aligned with the company's business objectives in Israel.
Conduct assessments of the local healthcare environment, payer landscape, and regulatory requirements to inform strategy development.
Collaborate with cross-functional teams to integrate market access considerations into product development and commercialization plans.
Identify opportunities and potential risks related to market access and develop mitigation strategies.
Reimbursement and Pricing:

Lead the submission and negotiation process for product reimbursement with relevant governmental authorities and health insurance industry in Israel. The Market Access Director Responsible to plan and lead all aspects of Health basket process and coordinate the cross-functional team for timely preparation to secure NHB inclusion.
Design and execute the PRA (Pricing & Reimbursement Affairs) Governance and the PRA Roadmap.
Develop pricing strategies to maximize product value while ensuring affordability and market competitiveness.
Setting optimal pricing and contracting strategy per market segments
Conduct pricing and reimbursement analyses, including health economic evaluations, to support pricing and reimbursement decisions.
Stay updated on pricing and reimbursement regulations and guidelines in Israel and provide guidance to internal stakeholders.
Acting as a functional leader for market access activities that include, but are not limited to, assessing market access needs/trends, and developing and executing required market access strategies to optimize market access, adoption, and commercial success.
Ensuring robust pricing practices, tendering, contracting protocols and operations to ensure efficient and compliant organization.
Contributing to annual brand planning by providing robust analysis and a strong payer value proposition and to forecasting, business planning and budgeting processes
Demonstrate competency in the use of business analytics to evaluate profit/loss of business deals.
Create and develop quantitative business cases to support contracting efforts in partnership with Affiliate finance team.

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.

The Senior Agentic Systems Engineer is a hands-on engineer who designs, builds, and operates AI-powered tools and workflows for engineering teams.
Were looking for builders who are not only users of AI tools, but can design autonomous agentic systems, optimize model usage, create reusable agents and workflows, and orchestrate complex multi-step work across multiple tools and agents.
Youll be a one-person-army builder: able to understand a problem, define the approach, build the backend, create a simple UI when needed, integrate APIs, connect agents, automate workflows, and deliver working tools quickly.
How will you make an impact?
Build centralized AI-powered tools for engineering teams.
Create and maintain agents, skills, hooks, MCP servers, plugins, and workflow automation.
Design autonomous agentic systems for internal engineering use cases.
Build multi-step AI workflows across code, documentation, Jira, GitHub, CI/CD, and internal systems.
Build tools for PR review support, test generation, documentation updates, spec creation, codebase understanding, and developer productivity.
Learn from local teams and convert successful solutions into reusable centralized assets.
Integrate AI tools with GitHub, Jira, Confluence, CI/CD, internal portals, and engineering systems.
Optimize AI workflows for cost, latency, quality, and reliability.
Apply token economy thinking when designing agents, prompts, MCP usage, RAG flows, and tool integrations.
Contribute to the internal AI marketplace and reusable asset catalog.
Work directly with engineering teams, collect feedback, and iterate quickly.