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abra Professional Services is seeking a Senior Full Stack Developer to join a leading cloud-based SaaS product team. In this role, you will develop end-to-end features, design scalable backend services, and contribute to architecture, performance, and code quality within a modern R&D environment. Key Responsibilities:
* Develop scalable components in a multi-tenant SaaS platform
* Build high-performance backend services using Node.js and TypeScript
* Design and manage PostgreSQL databases
* Write unit and integration tests and support CI/CD processes
* Collaborate closely with Product, backend, and QA teams

Were looking for a Backend Engineer to join our core R&D team in Tel Aviv - someone with strong backend fundamentals, experience in large-scale systems, and a modern, AI-assisted development mindset.

What Youll Be Doing
Help drive the adoption of AI-assisted development practices across the R&D organization by sharing knowledge, defining best practices, and leading by example.
Own and evolve core backend services in a mission-critical, AI-driven large-scale SaaS platform powering global enterprise operations.
Design, develop, and maintain production-grade backend services handling millions of real-time transactions daily.
Build and enhance algorithm-based (AI and others) components that support intelligent decision-making and real-time optimization.
Use AI tools as a first-class part of your daily development workflow - including design exploration, coding, refactoring, debugging, testing, and documentation.
Take part in architectural discussions and influence system design in a complex distributed environment.
Design and lead robust testing strategies to ensure stability, scalability, and security.
Explore and introduce new technologies, tools, and development patterns - with a focus on improving developer productivity, system quality, and delivery speed.
Collaborate closely with engineers, product managers, and data experts across global teams.

It starts with you - a technical leader whos passionate about database systems and growing high-performing teams. You care about query performance, uptime, data durability, and operational excellence. Youll lead the Datastores team in operating, tuning, and scaling the database engines that serve the platform - from PostgreSQL to Elasticsearch, Redis to vector databases, across cloud and on-prem environments.
If you want to lead a team that keeps the database engines running for mission-critical AI systems, join our companys mission - this role is for you.
The Responsibilities
Lead and grow the Datastores team - hiring, mentoring, and developing engineers while fostering a culture of operational excellence.
Own database reliability and availability - ensuring systems meet demanding SLAs for government and national-scale customers.
Drive performance tuning and optimization - query analysis, index strategies, configuration tuning, and resource optimization across all database engines.
Establish operational practices - backup/recovery procedures, disaster recovery, replication strategies, and failover automation.
Plan and execute capacity management - monitoring growth, forecasting needs, and scaling databases ahead of demand.
Lead incident response for database issues - troubleshooting, resolution, and post-incident improvements.
Enable new capabilities - evaluating, deploying, and operating new database technologies including vector databases for AI workloads.
Partner with Data Platform, Data Engineering, Engineering, and Security teams to align database operations with platform needs.
Define and uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate on schema evolution, partitioning, and safe replay/backfills.
Integrate with catalog and lineage systems - surfacing ownership, change history, and impact analysis for critical datasets and collections.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to prioritize performance, durability, and evolution of data stores across workloads.

It starts with you - an AI Engineering Team Lead responsible for leading a team building production-grade agentic systems. This role combines hands-on technical leadership with people management, ownership of architecture, delivery, and quality across agents, MCP tools, agentic workflows, RAG systems, and evaluation.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Lead and mentor a team of AI Engineers building agentic systems and MCP tools.
Own technical direction for agent architectures, workflows, and LLM evals.
Review designs and code; ensure production readiness, reliability, and security.
Drive adoption of frameworks such as LangChain, LangGraph, or equivalent.
Set standards for RAG pipelines, vector databases, and retrieval quality.
Partner with product and platform teams on roadmap, scope, and delivery.
Balance hands-on contribution with people management and execution.
Build a culture of strong engineering practices, measurement, and iteration.

It starts with you - a senior AI engineer focused on building production-grade agentic systems: autonomous agents, MCP tools, agentic workflows, and rigorous evaluation.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Design and build single- and multi-agent systems with planning, memory, and tool use.
Implement and operate MCP tools and servers with secure schemas and permissions.
Build agentic workflows using LangChain, LangGraph, or equivalent frameworks.
Integrate LLMs via SDKs; manage prompts, structured outputs, and tool calling.
Define and run LLM evals (quality, correctness, latency, cost, regressions).
Add observability and reliability (logging, tracing, retries, state management).
Optimize performance and cost; take systems to production.
Mentor engineers and establish agentic best practices.

Were looking for a Senior Full Stack Frontend-oriented Engineer to join our core R&D team in TLV - to lead frontend architecture, build highly responsive real-time experiences, and make a real impact on a high-performance, high-availability production environment.

Stuff youll be doing:

Own and evolve core frontend applications in a mission-critical, large-scale SaaS platform that powers global enterprise operations.
Design and build complex, real-time user interfaces that visualize and control large volumes of operational data.
Develop high-quality, production-grade code using modern React, TypeScript, and state management patterns.
Lead frontend architecture decisions in a monorepo environment, focusing on scalability, performance, and maintainability.
Collaborate closely with backend engineers, product managers, designers, and data teams to deliver end-to-end solutions
Define and drive front-end best practices - testing strategies, performance optimization, code quality, and developer experience.
Explore and adopt new technologies, tools, and patterns that improve frontend performance, reliability, and development velocity.

It starts with you - ML Engineering Team Lead responsible for leading a team delivering end-to-end ML systems. This role combines people management with ownership of model training, evaluation, deployment, and ML platform standards
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Lead and mentor ML Engineers delivering production ML systems.
Own technical direction for model architectures, training pipelines, and evals.
Review designs and code; ensure scalability, reliability, and data quality.
Define standards for experimentation, reproducibility, and monitoring.
Partner with product and platform teams on roadmap and prioritization.
Balance hands-on technical contribution with people management.
Build a culture of measurement, rigor, and continuous improvement.

It starts with you - an engineer driven to operate database systems at the highest level of reliability and performance. You care about query latency, uptime, data durability, and getting paged as little as possible. Youll operate, tune, and scale the database engines that serve the platform - from PostgreSQL to Elasticsearch, Redis to vector databases, across cloud and on-prem environments.
If you want to run the databases that power mission-critical AI at national scale, join our companys mission - this role is for you.
The Responsibilities
Operate and maintain database systems - PostgreSQL, Elasticsearch, Redis, MongoDB, vector databases, and others across cloud and on-prem.
Own database reliability - high availability configurations, replication, failover automation, and SLA adherence.
Drive performance tuning - query optimization, index design, configuration tuning, and resource profiling to meet latency and throughput targets.
Execute operational procedures - backup/recovery, disaster recovery testing, upgrades, migrations, and capacity scaling.
Lead incident response for database issues - troubleshooting production problems, root cause analysis, and implementing preventive measures.
Build monitoring and alerting - dashboards, metrics collection, slow query analysis, and proactive capacity alerts.
Enable new capabilities - deploying and tuning vector databases for AI workloads, evaluating new database technologies.
Collaborate with Data Platform, Data Engineering, Engineering, and Security teams on database operations and best practices.
Uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate safe schema evolution, partitioning, and replay/backfill practices.
Expose catalog and lineage signals - ownership, change history, and impact analysis - to improve trust and safe consumption for downstream users.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to balance performance, durability, and evolution across workloads.

It starts with you - a senior ML engineer responsible for building, training, evaluating, and operating machine learning systems in production. The role focuses on data pipelines, model training, experimentation, evaluation, and scalable deployment.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Design, train, and evaluate ML models for production use.
Build and maintain data pipelines for training, validation, and inference.
Own experimentation workflows: feature engineering, training runs, and comparison.
Implement model evals, monitoring, and drift detection.
Package and deploy models to production systems.
Optimize training and inference performance, cost, and reliability.
Collaborate with data, platform, and product teams.
Mentor engineers and promote ML engineering best practices.

It starts with you - an engineer driven to build resilient, automated infrastructure that enables teams to move fast with confidence. You care about operational excellence, developer experience, and reliability at scale. Youll architect and operate the compute and networking infrastructure that powers our AI platform - from CI/CD pipelines to Kubernetes clusters to observability systems - across cloud and on-prem environments.
If you want to build infrastructure that powers mission-critical AI systems at national scale, join our companys mission - this role is for you.
The Responsibilities
Architect and operate Kubernetes-based infrastructure across AWS and on-prem environments, ensuring high availability, security, and performance.
Design and maintain CI/CD pipelines for application and service deployments with automated testing, security scanning, and rollback capabilities.
Drive infrastructure-as-code practices for compute and networking - building reproducible, auditable, and version-controlled infrastructure.
Own reliability and incident response - establish SLOs, build alerting systems, lead incident resolution, and drive post-incident improvements.
Enable AI-native operations - support agentic deployment pipelines, self-healing infrastructure, and secure sandboxing for model experimentation.
Build and maintain observability systems - metrics, logging, tracing, and dashboards that provide visibility into system health.
Optimize infrastructure cost and performance - right-size resources, implement auto-scaling, and identify efficiency opportunities.
Collaborate with Engineering, Data Platform, Data Engineering, and Security teams to align infrastructure with platform needs.
Shape infrastructure characteristics that support data freshness, correctness, and low-latency pathways for AI training/inference, retrieval, and agentic workflows.
Contribute paved-road tooling - reusable CI/CD patterns for services, IaC modules for compute and networking, and runbooks - that streamline delivery across teams.
Collaborate with Engineering, Data Platform, Data Engineering, Security, Product, AI/ML, Data Science, and Analytics to anticipate and meet cross-functional needs.

Were looking for a Senior Program Manager to own the execution of our Sovereign AI roadmap end-to-end. Youll sit within the Product group and act as the connective bond between Data Science, Engineering, and Product - making sure complex, cross-functional initiatives ship on time and at the quality bar our customers expect.
If you are an unblocker, enjoy making tough tradeoff calls, and drive accountability across the board, your place is with us. Youll manage multiple parallel workstreams across verticals (Security, Health, AML, and more), platform, and AI/ML domains- and youll be the person everyone relies on to know and manage where things stand and what is about to happen next.
The Responsibilities
Own and manage the full lifecycle of Sovereign AI projects from planning through delivery. Track milestones, dependencies, and risks across multiple concurrent workstreams.
Drive cross-functional alignment, and work daily with Data Science, Engineering, Product, and Design teams to ensure same direction. Break down silos and surface early mitigation.
Maintain clear, accurate visibility into project status, blockers, and timelines. Communicate proactively to stakeholders and management.
Identify and solve risks, by own and drive resolution.
Work closely with senior leadership and domain leads to ensure roadmap priorities reflect strategic goals.
Translate execution-level realities into clear decision points - when tradeoffs need to be made, you frame the options and drive alignment.
Interface with internal leadership and external government stakeholders to align on scope, timelines, and priorities. Keep information flowing in both directions.
Continuously refine processes, rituals, and tools to make the team more effective without introducing unnecessary overhead.

We are developing state-of-the-art LiDAR sensors and advanced perception software for the automotive industry. We are looking for a Senior System Integration Engineer to join our fast‑paced, innovative team responsible for bringing complex LiDAR systems together into a cohesive, high‑performance product. This role is ideal for a hands‑on who thrives on multidisciplinary problem‑solving, system bring‑up, and driving features from early integration through customer delivery.
Responsibilities:
Lead system integration activities across the LiDAR development lifecycle, from initial bring‑up through validation and customer deployment.
Integrate hardware, firmware, software, tools and algorithms into a unified LiDAR system, ensuring seamless functionality across disciplines.
Plan and execute system‑level integration tests, debug complex issues, and drive root‑cause analysis with cross‑functional teams.
Develop and maintain integration workflows, test setups, and automation tools to accelerate development and validation.
Collaborate on requirements refinement, system architecture discussions, and design reviews to ensure integration readiness.
Build Python‑based tools for data analysis, test automation, and rapid prototyping to support integration and characterization activities.
Support development processes aligned with Automotive SPICE and other automotive quality standards.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company'sAI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Conduct cutting-edge research in natural language processing and large language models.
Design, train, and optimize large-scale neural network models for advanced applications.
Transition research projects from ideation through deployment and scaling.
Collaborate closely with cross-functional teams, including domain experts, product managers, and engineers, to deliver impactful AI solutions.
Define and contribute to the AI and NLP product roadmap.

We are developing state-of-the-art LiDAR sensors and advanced perception software for the automotive industry. We are looking for a Senior System Engineer to join our fast-paced, innovative team developing LiDAR systems for autonomous vehicles. We are looking for a talented hands-on contributor and feature owner, to lead multi-disciplinary systems development and integration, from KPI and data analysis and algorithm prototyping to customer delivery.
Responsibilities
Lead system engineering activities across the LiDAR development lifecycle, from concept through integration and validation.
Develop LiDAR features including algorithms, calibration methods and post-processing solutions.
Perform system-level testing, characterization and modeling.
Contribute to requirements definition, system design, and design reviews with cross-functional teams.
Develop Python- based simulations, prototypes, and automation tools for rapid proof-of-concept and laboratory equipment control.
Lead development processes according to Automotive SPICE standards.