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Required AI Platform Engineer
Position Overview:
We're assembling a small-scale team of innovators committed to a transformative mission: advancing generative AI from conceptual breakthrough to tangible product reality. As an AI Platfrom Engineer, you will be a critical architect of the technological infrastructure that brings our most ambitious GenAI concepts to life, transforming our digital intelligence solutions through cutting-edge AI innovation.
Build advanced AI platform that operates both as a cloud SaaS and as a fully self-contained on-prem / edge deployment, designed for privacy-sensitive and security-critical environments, at the intersection of backend development, AI integration, DevOps, and open-source systems engineering.
You will be part of the core team responsible for adapting, hardening, and operating our SaaS architecture in on-prem and single-node environments (on Prem servers, laptops). Working closely with architecture and product management and play a key role in making complex AI systems deployable, reliable, and operable outside the cloud.
Key Responsibilities
Platform & Application Engineering:
Adapt cloud-native AI services to on-prem and edge deployments (single node, no managed cloud services).
Build and maintain full-stack components: Backend APIs (Python / Node.js), Lightweight UIs or internal tools when needed, Ensure services are stateless, configurable, and portable across environments.
AI & Open-Source Integration:
Integrate and operate open-source LLMs for:
RAG pipelines
Agentic workflows
Tool calling and orchestration
Work with: Embedding models, Vector databases (local and embedded modes), Analytical engines (e.g., embedded SQL / columnar systems), Optimize inference for CPU / single-GPU environments (quantization, batching, caching).
DevOps & Runtime Engineering (Strong Focus):
Package services into portable Docker containers usable in:
On-prem servers (Kubernetes)
laptop / edge devices
Implement in-process scaling strategies (worker pools, task queues, batching).
Build simple, reliable deployment and startup flows (no heavy orchestration).
Manage configuration, secrets, logging, and observability in constrained environments.
Systems & Reliability:
Design for: Offline operation, Limited resources, Predictable performance
Implement graceful degradation between: SaaS mode, On-prem server mode, Single-node / laptop device mode, Debug complex interactions across AI models, storage, and runtime systems.

What will you do
Lead the design, development, and optimization of core backend services using Java and modern JVM technologies.
Own the architecture and performance of mission-critical components: data ingestion, processing pipelines, distributed services, storage abstractions, and internal frameworks.
Drive large-scale refactoring, modernization, and reliability initiatives.
Establish and maintain high engineering standards, code quality, and best practices across the entire R&D
Build and improve systems that handle high throughput, low latency, and massive data scale.
Work closely with DevOps/SRE/R&D teams to strengthen infrastructure, observability, automation, and deployment practices.
Diagnose complex production issues spanning multiple services, layers, and technologies.
Continuously improve system performance, resource efficiency, and cost footprint.
Lead, mentor, and grow a team of backend engineers and define best practices for the entire R&D
Conduct technical reviews, coaching, and hands-on training to elevate the teams skill set and the R&D
Collaborate with cross-functional teams to understand platform needs and translate them into a clear engineering roadmap.

As our DevOps Team Lead you will work with cutting-edge technologies and take ownership of building and evolving a scalable, globally distributed infrastructure.
In this role, you will:
Lead and mentor DevOps engineers, providing technical guidance, setting best practices, and supporting professional growth.
Collaborate closely with engineering, security and data teams to deliver scalable and reliable solutions.
Design, architect, deploy, and maintain robust cloud infrastructures across AWS and Azure.
Own and continuously improve CI/CD pipelines to support automated deployment, testing, and scaling across multiple environments.
Implement and manage monitoring, logging, and alerting solutions to ensure system reliability and performance.
Provide hands-on troubleshooting and resolution of complex infrastructure issues across production, staging, and development environments.
Promote operational excellence, security best practices, and cost optimization across the cloud environment.
Act as a technical leader and decision-maker, balancing hands-on execution with strategic planning.

Were looking for a highly skilled AI Engineer to join our Forensic Research Group and help shape the next generation of intelligent forensic platforms.
Youll work at the intersection of Generative AI, agentic systems, and real-world data, building advanced capabilities for both internal tools and production systems that transform how complex data is analyzed and understood.
Using state-of-the-art models and emerging AI paradigms, youll design systems that move beyond traditional pipelines into autonomous, adaptive workflows.
Youll help define the future of agentic decoding - where AI doesnt just assist, but actively reason, explore, and uncover critical evidence, impacting millions of cases worldwide.
If youre excited about building impactful AI systems and solving complex, messy problems, this role is for you.
What Youll Do:
Design and build AI-driven and agentic solutions to parse, analyze, and interpret data from forensic extractions (including mobile devices)
Develop GenAI-powered capabilities for understanding, structuring, and reasoning over unstructured data
Combine LLMs, multi-agent systems, and heuristic approaches to improve data identification, classification, and insight generation
Build autonomous and semi-autonomous pipelines that transform manual and brittle workflows into scalable, intelligent systems
Work with real-world, noisy datasets to uncover patterns, anomalies, and meaningful structures
Collaborate closely with forensic researchers and engineers to translate domain expertise into AI-native solutions
Influence system architecture, tooling, and the evolution of internal AI platforms and agent frameworks
Evaluate, fine-tune, and integrate state-of-the-art models (LLMs, multimodal models, etc.) for complex real-world problems.

Required AI Architect
Position Overview:
As the AI Architect for our SaaS Platform & Products, you will define and drive the end-to-end AI architecture that powers our cloud AI platform and product capabilities, while ensuring strong alignment with security, privacy, reliability and cost-efficiency requirements. You will partner closely with engineering leaders, product management, data science, security and operations to translate business needs into a scalable, governed and AI platform that accelerates innovation across multiple product lines.
This is a hands-on architecture role: you will set technical direction, run architectural reviews, and build prototypes to validate technology choices and de-risk delivery.
Key Responsibilities:
Own the AI Vision: Take end-to-end ownership of the AI architecture across, including our cloud AI platform, agentic AI infrastructure, and on-prem/hybrid AI deployments.
Architect an AI Platform for SaaS Products: Define reference architectures and shared building blocks (e.g., AI gateways, orchestration runtimes, memory/RAG systems, vector search, evaluation frameworks, observability, and guardrails) that can be adopted consistently across products and teams.
Cost Optimization and Scalability: Provide architectural leadership to ensure AI systems are designed for cost efficiency and scalability, actively identify and implement opportunities to optimize cloud spend (FinOps), improve utilization, and meet latency/SLO targets.
Product-Centric Collaboration: Collaborate with engineering, product, data science, security, and operations teams to translate product requirements and business needs into a strategic AI architecture that drives measurable product value.
Technology Evolution and Prototyping: Evaluate new technologies, tools, and methodologies to continuously improve our AI systems, build prototypes and proof-of-concepts to validate approaches and accelerate decision-making.
Technical Reviews, Standards and Mentorship: Lead technical design reviews and provide guidance on best practices and emerging technologies. Act as a technical authority and mentor, fostering a culture of engineering excellence and pragmatic delivery.
AI Governance, Privacy and Security: Ensure AI capabilities comply with data privacy, security, and ethical AI guidelines. Partner with security and legal stakeholders to implement governance controls and risk mitigations appropriate for regulated environments.

We're seeking a talented, versatile, and highly independent Full Stack Engineer to join our engineering team.You will drive end-to-end development of technical foundation and platform services that empower all of our teams, influencing both product capabilities and technical decisions.
Responsibilities:
Lead development processes from ideation to production
Develop, implement, and maintain the platform's foundational services, including web applications, APIs, and essential internal solutions.
Collaborate with multiple engineering teams, product, and medical teams across the organization
Build a customer-centric product with a deep understanding of the complex healthcare industry

As a Senior Software Engineer for our company Asset Beacon, you will be a key technical contributor driving the development of innovative solutions for commercial real estate asset management. Working within a collaborative engineering team, you will take ownership of complex technical challenges across the full development lifecycle, designing and implementing robust, scalable solutions that translate business requirements into actionable insights and streamlined experiences for real estate professionals.
You will collaborate closely with the engineering and data team, product managers, and global distributed teams to build and enhance both frontend and backend components. A significant focus involves exploring and implementing AI-driven capabilities, identifying opportunities to integrate artificial intelligence for enhanced automation, predictive analytics, and intelligent decision-making tools. Your full-stack development skills and architectural mindset will be essential in advancing the platform's technical capabilities while contributing to a culture of innovation and continuous improvement.
This role offers the opportunity to make a direct impact on the real estate industry through cutting-edge technology, working with modern development practices and contributing to solutions that help optimize asset performance and drive business value for commercial real estate professionals worldwide.
Responsibilities:
General responsibilities
Build and maintain infrastructure for the platform and manage aspects of the release cycle
Conduct regular code reviews, provide technical guidance, and support professional development of team members
Manage planning, task allocation, and technical delivery timelines
Foster a collaborative, innovative culture within and across teams
Stakeholder Management
Communicate technical constraints, opportunities, and progress to non-technical stakeholders
Collaborate with internal developers and external partners to align on development
roduct Collaboration
Coordinate closely with the product team to understand requirements and deliver solutions
Develop features from conception through release with attention to user experience
Ensure technical solutions address business requirements
Our Technologies:
Frontend: VueJS, SASS/CSS
Backend: Python, Django, FastAPI
Database: SQL with ORM integration
DevOps: Docker, Kubernetes, Helm, GitHub Actions
AI Tools: Cursor, OpenAI Agents SDK, LLMs.

We're hiring for a new AI Engineering team in Tel Aviv, and you would be the first infrastructure hire. You will own the platform layer for AI agents the team builds: deployment architecture, observability, and production reliability.
The team's first two projects: an agent that automates internal governance processes (vendor reviews, security questionnaires, tool provisioning), and an agent that helps engineering teams prepare for architecture reviews. Both integrate with external APIs (LLM providers, OneTrust, ServiceNow), handle structured decision logic, and manage sensitive data flows with audit requirements.
Highlights
- Greenfield, but with real constraints. You're building on Azure/AWS with enterprise security requirements. The challenge is designing deployment and observability for LLM-backed services. You need to track output quality, cost per invocation, and model drift.
- Enterprise complexity, startup autonomy. Ownership and greenfield environment of a startup, with the integration challenges of a Fortune 200: connecting AI services to real enterprise systems.
- More than infrastructure. Your core is SRE, but you'll also write agent code in TypeScript and Python, work with data pipelines, and ship features alongside the team.
What the Work Looks Like
AI Service Infrastructure - Design and maintain deployment and release infrastructure for AI agents. The stack is cloud-native (Azure/AWS), with services that call LLM APIs, connect to enterprise systems, and handle structured data.
Observability & Reliability - Build monitoring and observability for AI services. Ensure model response quality doesn't degrade silently by tracking errors, logging cost spikes, and monitoring upstream API changes.
Security & Compliance - These agents handle sensitive workflows with elevated security requirements. You will work with our company's security team on standards, but you own how they're implemented in the infrastructure.
Developer Experience - Create tooling that makes it easy for the team to build, test, and deploy. The patterns you set become the team's defaults.

We are looking for a Tech Lead to serve as the technical "center point" for our Population Health engineering group. In this high-leverage, non-managerial role, you will float between multiple feature teams to solve the most complex architectural challenges, unblock technical debt, and ensure our systems scale as fast as our data does.
You aren't just building features; you are building the engine that powers them. You will spend 70-80% of your time hands-on-coding, architecting, and creating the shared tools that make every other engineer in the group faster and more effective.
Responsibilities:
Architectural Glue: Own the technical "contracts" (APIs) between teams to ensure seamless integration across the Pop Health ecosystem.
Performance & Scalability: Optimize our engines and application layer to handle massive clinical datasets, ensuring our UI remains snappy and our backend is resilient.
Data Pipeline Strategy: Lead the design and implementation of scalable BI data pipelines and robust ETL/ELT processes that transform complex clinical data into actionable insights.
Force Multiplier: Identify friction points in the development lifecycle and build internal tools or libraries to increase engineering velocity.
Technical Stewardship: Provide high-level code reviews, author RFCs for major architectural shifts, and mentor senior engineers through complex technical hurdles.

We are actively seeking a hands-on Implementation Engineer to play a vital role in the success of our customers. Standing at the intersection of technology and customer success, you will be responsible for translating AI and data requirements into seamless integrations with our customers' EMRs and clinical workflows.
In this role, you will own the end-to-end technical onboarding lifecycle - from initiation to go-live. You will serve as the primary technical voice for our customers' IT stakeholders and collaborate closely with our Product, R&D, and Medical teams to ensure frictionless integrations.
Responsibilities:
Lead Technical Onboarding: Own the full technical implementation lifecycle for new customers, ensuring projects are delivered on time, within scope, and meet high-quality standards.
EMR Integration & Configuration: Execute hands-on technical integration efforts. You will configure workflows, validate data integrity, and ensure interacts seamlessly with various EMR environments.
Stakeholder Management: Act as the primary technical point of contact for customer IT teams (CTOs, IT Managers, Analysts). Build strong relationships to troubleshoot issues and facilitate smooth collaboration.
Technical Subject Matter Expert: Represent the technical aspects of the platform in customer interactions. Demonstrate deep product knowledge to solve complex workflow challenges.
Cross-Functional Collaboration: Work closely with Customer Success, Product, R&D, and Medical teams to advocate for customer needs and streamline the feedback loop between the field and engineering.
Process Optimization: Help design and develop automation tools, runbooks, and frameworks to streamline integration processes and improve scalability.

We are looking for an experienced Product Manager to lead Diagnosis Insights domain - responsible for the intelligence layer that powers our clinical suggestions and diagnosis capture experience across patient populations.
This role sits at the intersection of clinical reasoning, data, and AI. You will define, refine, and scale the logic behind diagnosis insights - owning the end-to-end experience from medical modeling through how suggestions are surfaced to clinicians and others. Your mission is to drive superior accuracy, broad coverage, and measurable impact across patient types and care models.
This position is ideal for a PM who combines strong analytical and technical depth with clinical intuition, and who is excited to build AI-powered products that influence real-world clinical decisions at scale.
Responsibilities:
Define and drive the product roadmap for Diagnosis Insights domain. Own the long-term vision for diagnosis suggestion ecosystem - from medical logic and model strategy to how insights are presented, prioritized, and acted upon by clinicians.
Own and define KPIs, including model coverage and precision, alongside end-user adoption metrics (e.g., physician address rate).
Lead core product interfaces: Own the insights experience on both the physician and administrative teams' interfaces.
Work closely with Engineering, Data Scientists, Medical Experts while actively engaging with clients and end users to deeply understand their desired outcomes, and validate new ways to improve our suggestion algorithm.
Translate customer and business requirements into PRDs, technical specifications, and logical flows for the Engine and Core teams.
Explain complex medical logic in simple, non-technical language to internal stakeholders (Support, CSM, Implementation teams) and support generate internal product documentation.
Use SQL and analytical skills to interrogate data, evaluate logic performance, and validate improvements.
Own and manage the product backlog, prioritizing requests based on customer impact, business goals, and urgency.