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We're hiring an exceptional Applied AI Scientist to join our team!

In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across Tipalti's core functions - Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems.


In This Role, You Will Be Responsible For


Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions - including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support).
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails, and audit trails suited for an enterprise fintech environment.
Knowledge Systems: Building and maintaining RAG pipelines that ground agents in proprietary knowledge - product documentation, customer data, financial records, and internal playbooks - using vector databases, hybrid search, and re-ranking.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI - from data preprocessing through product deployment.

we are looking for a Software Engineering Manager (SRE Team).
In this role, you will be responsible for:
Lead a distributed team of 3 SRE engineers as a part of Global SRE group and report to the Director of SRE &DBOps.
Drive incident response and post-mortem processes, fostering a culture of continuous improvement.
Design, build and improve internal tools and automation software to make maintaining production services easier and safer.
Lead reliability-focused practices such as SLO (Service Level Objective) design and implementation, Failure Analysis, Load and Capacity Planning, Service Reviews, Architecture Designs, Incident Postmortems, and others.
Participate in the on-call rotation, providing expertise and support during critical system incidents and ensuring timely resolution.
Ensure high technical standards and overcome various technological challenges.
Be accountable for the team's output, empowering and coaching team members, setting goals, and ensuring engagement.
Embrace values of independence, natural curiosity, ownership, and continuous improvement.

our company's ML Platform group builds and operates the core infrastructure that powers large-scale AI workloads across on-prem bare-metal GPU clusters and multi-cloud environments. Our goal is to deliver the modern infrastructure and tooling that accelerates our company's entire algorithm development lifecycle - from a researcher's first experiment to a production deployment.
We are a small, independent group of engineers with diverse skills across software, infrastructure, and systems. We set the standards, build the cross-company products, and take end-to-end ownership of everything we ship.
What will your job look like?
Design, develop, and maintain the Python framework that enables algorithm developers across our company to train, validate, quantize, and deploy deep learning models - locally, on-prem, and across cloud providers - through a single unified interface
Build high-performance data streaming libraries that feed large-scale distributed training pipelines in Rust with Python interfaces
Set the standard for reliable, reproducible research at scale - experiment tracking, configuration management, checkpoint handling, and multi-node training
Work directly alongside algorithm researchers to understand friction, propose solutions, and ship them - without layers of process in between
Contribute to open source when the right fix/feature belongs upstream.

The SW validation team plays a key role in enabling the next generation of autonomous driving technologies. In their primarily Python-based development environment, they are responsible for developing and maintaining test content for the autonomous vehicle brain, supporting complex end-to-end validation flows across the system.
As part of the full autonomous driving pipeline, they work closely with cutting-edge technologies and gain direct exposure to the real-world impact of their work - helping bring some of our companys most advanced autonomous driving capabilities from development into reality.
What will your job look like:
Be the technical lead of the team that is responsible for the development of test content (mostly in Python) for the autonomous vehicle system and E2E flows
Review and approve system architecture requirements
Design and implement complex test solutions
Enforce compliance with autonomous vehicle industry standards.

The Road Algorithm team is responsible for one of the most critical and challenging tasks in autonomous driving - detecting and understanding the drivable road. Our work leverages Deep Neural Networks and geometric modeling to deliver reliable and high-quality road perception for autonomous vehicles.
We are looking for an Expert Deep Learning Research Engineer who will both drive independent deep learning research and collaborate closely with other developers to help unlock new directions, solve complex challenges, and elevate the teams algorithmic capabilities.
What will your job look like:
Conduct hands-on research and development of deep learning algorithms for road understanding, drivable area detection, and scene structure modeling
Lead exploratory investigations into new architectures, training strategies, and data utilization methods
Join forces with other developers to troubleshoot difficult problems, introduce new ideas, and guide technical decisions
Own projects end-to-end - from concept and experimentation to integration and scalable deployment.

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.
This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C++, ML infrastructure, model integration, performance optimization, and production delivery.
** The role includes working on-site at our Jerusalem office several days per week.
What will your job look like:
Lead end-to-end development of features - from design and implementation to integration, testing, and deployment
Build ML pipelines for data-based diverse dataset creation and efficient model inference
Design data selection and sampling strategies to ensure coverage of rare and critical scenarios
Partner with algorithm teams to translate model weaknesses into data curation criteria
Develop validation and diagnostics to measure dataset quality-not just pipeline health but training effectiveness
Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing
Bring models from research/prototype stage into robust, production‑ready deployments
Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments
Contribute to deployment flows (e.g., model conversion, profiling, optimization)
Build and improve CI/CD pipelines, automated testing, and development workflows.

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.
This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C++, ML infrastructure, model integration, performance optimization, and production delivery.
What will your job look like:
Lead end-to-end development of features - from design and implementation to integration, testing, and deployment
Build ML pipelines for data-based diverse dataset creation and efficient model inference
Design data selection and sampling strategies to ensure coverage of rare and critical scenarios
Partner with algorithm teams to translate model weaknesses into data curation criteria
Develop validation and diagnostics to measure dataset quality-not just pipeline health but training effectiveness
Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing
Bring models from research/prototype stage into robust, production‑ready deployments
Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments
Contribute to deployment flows (e.g., model conversion, profiling, optimization)
Build and improve CI/CD pipelines, automated testing, and development workflows.

we are looking for a driven and technically fluent Product Manager to join the MECI Group within the Software Engineering organization. The MECI Group enables our companys algorithmic development flow by building scalable CI, build, test, and AI-driven tooling that supports the full development lifecycle. Our platforms allow our company to scale efficiently and increase development velocity, while maintaining high standards of reliability, collaboration, and developer well-being. As a Product Manager in MECI, you will own and evolve core internal platforms that are foundational to how our company develops, validates, and delivers algorithms. This role sits at the intersection of engineering, infrastructure, and developer experience, with broad impact across Algo, Validation, and Platform teams.
Why this role is unique
This role offers end-to-end ownership of products that are central to our companys development ecosystem. You will lead products spanning development workflows, build and test systems, platform services, and AI-assisted tooling, operating across multiple teams and technical domains. The role combines strategic product leadership with hands-on collaboration in a highly technical environment, where scale, performance, and reliability are critical. Youll work closely with engineering leaders and cross-functional stakeholders to identify high-impact problems, define clear priorities, and drive delivery of solutions that measurably improve productivity, platform stability, and developer experience.
What your job will look like:
Own the product vision, strategy, and roadmap for key MECI platforms and capabilities
Drive cross-organizational alignment on platform priorities, architectural evolution, and adoption strategy
Translate needs from Algo developers, Validation teams, CI users, and Infrastructure stakeholders into clear product requirements, specifications, and user flows
Lead the full product lifecycle - from discovery and problem definition, through design and implementation, to rollout, monitoring, and continuous improvement
Maintain ongoing engagement with users to deeply understand workflows, pain points, operational constraints, and opportunities for improvement
Partner closely with engineering leadership on prioritization, scope, and delivery, balancing short-term needs with long-term platform health
Contribute to building a culture of collaboration, ownership, and sustainable development, with attention to developer well-being.

we are looking for a Real-Time Embedded DSP Software Engineer to join the development of state-of-the-art automotive imaging radar technology.
Our vision is to bring new and cutting-edge automotive radar sensor solutions, while leveraging our companys assets and expertise in this field. Introducing best in class Radar sensor that would complement our companys end-to-end autonomous driving solution platform
You will be part of a winning team in a fast-paced startup-like environment, working on many different components of the entire system. You will have an opportunity to make an impact on the design and implementation of an innovative technology in its early stages.
What will your job look like?
Design, build and optimize software modules for production grade imaging-radar solution
Implement complex algorithms in a multi-core platform with high bandwidth with distributed memory
Work closely with algorithms teams to convert complex MATLAB code to efficient real-time environment.
Plan memory arrangement, data transfers and pipelining of computation, to maximize DSP utilization.

Which department will you join?
The Infra development team is a part of Software Algorithm (SW Algo) Department at our company responsible for the software infrastructure and development algo utilities for autonomous driving algorithm code running on our company's platform. As part of the end-to-end autonomous vehicle flows, we get to see our code running in the most advanced algorithms and use cases, which are developed by our team and algorithm groups. The development environment is mostly based on C/C++ programming within computer vision domains.
As a Senior C++ Developer, you will play a key role in designing, building, and maintaining Algo utility and software infrastructure within the company's primary algorithmic flow.
** This role may offer the flexibility to work one day per week from our other sites, subject to seat availability.
What will your job look like:
Leading the development of high-performance applications using C++ and optimizing the existing codebase for efficiency and scalability
Collaborating with multiple departments in our company to acquire broad insights into algorithmic and technical details, ensuring seamless integration with the overall system
Debugging real-time oriented code while adhering to high standards of memory management and running-time requirements
Working closely with external algo teams and various departments in our company for requirement gathering and the correct integration of new features
Engaging with different environments in our company's software stack, including backend and middleware, to ensure the smooth operation of the software infrastructure
Opportunities to work on cutting-edge projects and technologies in the autonomous driving industry
Exposure to advanced algorithms and use cases, showcasing your expertise to a wide audience
Collaboration with a talented and passionate team of developers, algorithm engineers, and other professionals.

we are looking for an experienced Software and Integration Engineer to join the CTO group and take a key role in delivering robust, large-scale autonomous driving software.
The group is primarily focused on the decision-making module of our company's self-driving car. It leverages a wide range of algorithmic approaches, rigorous formal definitions, and mathematical modeling- enriched by insights drawn from large-scale data and real-world driving experience.
In this role you will play a key role in designing, building, and maintaining Algo utility and software infrastructure within the company's primary algorithmic flow.
What will your job look like:
Take part in technical design and decision-making, balancing performance, scalability, and maintainability.
Debugging real-time oriented code while adhering to high standards of memory management and running-time requirements.
Manage the groups software delivery, ensuring timely, high‑quality releases.
Opportunities to work on cutting-edge projects and technologies in the autonomous driving industry.
Working closely with external algo teams and various departments in our company for requirement gathering and the correct integration of new features.

You will be part of our company's REM department, which is responsible for the automatic High-Definition map-making process, a key technology in our autonomous driving and advanced driver-assistance systems.
This process involves running advanced algorithmic code in a massively parallel way, utilizing Big Data technologies, and managing a complex system that requires both technical depth and strategic thinking.
We are seeking a Backend & Data Engineer to join our Innovation Team within our Mapping Division. This role is best suited for engineers with strong system-level thinking, a can-do approach, and a hands-on mindset, with the ability to design, build, and optimize complex systems operating at scale.
What your job will look like:
Develop and maintain backend and data-processing components in large-scale systems
Design, implement, and optimize data pipelines and distributed processing flows
Work with large-scale storage systems (e.g., S3) and high-volume data access patterns
Optimize systems and code across multiple layers - from architecture to implementation
Identify performance bottlenecks, debug complex issues, and drive root-cause solutions
Work across teams and domains, reading, improving, and refactoring existing code
Take part in technical design and decision-making, balancing performance, scalability, and maintainability.

You will be part of our company's REM department, which is responsible for the automatic High-Definition map-making process, a key technology in our autonomous driving and advanced driver-assistance systems.
This process involves running advanced algorithmic code in a massively parallel way, utilizing Big Data technologies, and managing a complex system that requires both technical depth and strategic thinking.
We are seeking a Backend & infrastructure engineer to join our Innovation Team within our Mapping Division. This role is best suited for engineers with strong system-level thinking, a can-do approach, and a hands-on mindset, with the ability to design, build, and optimize complex systems operating at scale.
What your job will look like:
Develop and maintain backend and data-processing components in large-scale systems
Design, implement, and optimize data pipelines and distributed processing flows
Work with large-scale storage systems (e.g., S3) and high-volume data access patterns
Optimize systems and code across multiple layers - from architecture to implementation
Identify performance bottlenecks, debug complex issues, and drive root-cause solutions
Work across teams and domains, reading, improving, and refactoring existing code
Take part in technical design and decision-making, balancing performance, scalability, and maintainability.

The company's Software group is looking for an excellent experienced DevOps engineer to join the Software infrastructure team.
our company's software infrastructure CI Team is responsible for maintaining various CI flows and maintaining the high quality of the software and system products.
Your expertise will contribute to our ongoing intensive development process while maintaining live production.
Join us to make a difference in how the world drives!
What will your job look like?
Design, implement, and maintain CI infrastructure and automation tools to support scalable development.
Work hands-on with technologies such as Jenkins, GitLab, Kubernetes, Python, Groovy, and Bash.
Collaborate with multiple engineering teams to understand their CI/CD needs and provide high-quality solutions.
Lead technical improvements and proactively enhance system performance, scalability, and developer productivity.
Troubleshoot complex issues across infrastructure and code, and continuously drive innovation and process optimization.
Help shape a structured, collaborative, and improvement-driven engineering culture.

We are looking for a software engineer to build AI infrastructure that enables agentic workflows for DSP software development and legacy code maintenance.
The role focuses on developing code-aware AI systems that can reason about large embedded C/C++ codebases, particularly in DSP environments with custom instruction sets. You will design the infrastructure that allows AI agents to understand code structure, retrieve relevant context, analyze DSP kernels, and generate validated patches integrated into real development pipelines.
This is a unique opportunity to work at the intersection of agentic AI systems and real-world physical products, enabling AI-assisted development for complex embedded DSP software powering production hardware.
What will your job look like?
Build AI-driven developer infrastructure to support DSP software development workflows
Design code-aware retrieval systems combining structural program analysis with semantic search
Implement DSP-aware indexing pipelines that detect vector operations, loop kernels, accumulator flows, memory access patterns, and custom instruction usage
Design agent orchestration workflows for planning, code analysis, patch generation, and build/test validation loops
Integrate the AI system with build systems, compilers, and simulators to validate generated changes
Enable AI-assisted workflows for legacy code comprehension, dependency tracing, debugging, refactoring, and DSP kernel optimization.