Join team to build and extend the AI assistant embedded across our product suite. The platform is a production LLM agent system that's integrated into multiple host applications, backed by a RAG knowledge base and an evaluation-driven development workflow.

You'll work end-to-end: agent design, tool implementation, retrieval quality, integration into existing product UIs, cloud infrastructure, and evaluation/observability. The platform already ships to customers - you'll extend it, raise its quality bar, and help define where it goes next.

What you'll do

Design and evolve agents - build LLM agents with tool use, routing, and human-in-the-loop flows.
Implement tools and integrations - expose product capabilities to the agent, with multi-tenant context, via internal APIs and MCP servers.
Own retrieval quality - contribute to our RAG pipeline end-to-end: ingestion, embeddings, vector search, and reranking.
Define and evolve host integration contracts - collaborate with host application teams to integrate the assistant into product UIs built on different frontend stacks. You own the shared remote module and the integration API; host teams own their stacks.
Drive evaluation-led development - write evaluators (rule-based, LLM-as-judge, multi-turn), maintain CI eval gates, and use traces and feedback to debug production behavior.
Operate the platform - own deployments, observability, and the performance and cost of LLM-backed services.
Establish engineering practices** for AI-specific work: prompt versioning, eval coverage, testing, and code review.

As a Senior Data Infra Engineer, you'll be a key part of our data platform team, responsible for designing, building, and maintaining robust and scalable data pipelines. You'll work closely with data scientists, analysts, and server side engineers to ensure our data is reliable, accessible, and ready for analysis. Your expertise will be crucial in expanding our data warehouse and data lake capabilities, enabling us to deliver next-generation ad tech solutions.

Your mission will be to:

Develop and Optimize Data Pipelines: Design, build, and maintain ETL/ELT pipelines using Apache Spark to ingest, process, and transform large-scale datasets from various sources.
Manage Cloud Infrastructure: Architect and manage our data infrastructure primarily on Google Cloud Platform (GCP) or Amazon Web Services (AWS). This includes services like BigQuery, S3, GCS, EMR, and AirFlow.
Enhance Data Storage: Improve and manage our data warehouse and data lake solutions, ensuring data quality, consistency, and accessibility for business intelligence and machine learning applications.
Collaborate and Innovate: Partner with cross-functional teams to understand data needs and implement solutions that support new product features and business initiatives.
Ensure Data Integrity: Implement monitoring, alerting, and logging systems to maintain data pipeline health and ensure data accuracy.

We are looking for an Engineering Team Lead to lead the MLOps efforts - drive the development of an internal machine learning platform for a group of ML teams. This is a hands-on leadership role: you will guide a small team of MLOps engineers that builds the automation and infrastructure powering our research (R&D) workflows and runs our pipelines to production. You will take ownership of end-to-end initiatives and drive the team toward critical infrastructure and model-lifecycle milestones, while staying close enough to the code to set technical direction and raise the bar by example.
You will be responsible for building and maintaining the models and data pipelines behind our data science workflows, ensuring the accuracy, consistency, and efficiency of the data used for training and inference, working across structured and unstructured data from many sources on a large-scale, distributed platform.
Responsibilities:
Lead, mentor, and grow a team of MLOps engineers, owning delivery and technical quality.
Take end-to-end ownership of infrastructure and pipeline initiatives across the LMM group, from design through production.
Stay hands-on: contribute to design and code, review work, and set engineering standards.
Drive the team through critical milestones in ML model-lifecycle and infrastructure ownership.
Partner with R&D and other stakeholders to translate research needs into robust, scalable systems.
Help evolve the platform, including our ongoing migration from Dask to Ray.

We are looking for an experienced and hands-on ATE Engineer to design, develop, and maintain the data and software infrastructure supporting our Automated Test Equipment (ATE) environments. In this role, you will establish the database architecture, data pipelines, reporting tools, and infrastructure required for electronic card testing, system-level testing, and radar calibration of advanced radar systems. Key Responsibilities:
* Design and maintain the ATE database and software infrastructure.
* Develop data pipelines, APIs, and integrations for ATE systems.
* Build BI dashboards and reports for production and test data.
* Ensure data integrity, traceability, backup, and availability.
* Support deployment across production sites and secured networks.
* Collaborate with ATE, Production, IT, Quality, and Cybersecurity teams.

We are seeking a visionary Director of Engineering with a strong product mindset to lead the strategy, development, and scaling of our subscription management products.

As a Director of Engineering , you will...
Build, lead, and mentor multiple cross-functional teams of managers and developers to deliver a scalable and reliable product
Foster a culture of collaboration, automation, and continuous improvement within the engineering organization
Define and implement procedures and workflows that will enable rapid innovation while ensuring enterprise-grade quality of the delivered product
Own the AI enablement vision for your organization: identify where AI can meaningfully accelerate the software development lifecycle, build the roadmap, and drive hands-on execution
Act as a key partner to business stakeholders-product, sales, finance, and executive leadership-in translating business goals into engineering strategy and representing engineering priorities in company-wide decisions
Partner with engineering leaders, product teams, and business stakeholders to ensure successful product adoption by customers

We are looking for a Software Automation Engineer to join our QA team and to take part in the testing process from planning to execution.
Responsibilities:
Responsible for QA processes, testing and release to production of multiple SaaS products.
Build the test plan for the products.
Identify the risks and appropriate test coverage to validate new features as well as regression and develop test plans and cases.
Lead the test execution and preparation for release.
Execute test cases, manually or in an automated fashion, capture and analyze the results, document issues and prepare test reports.
Work with the R&D and Product to deliver high-quality tested SaaS products.
Write test automation for APIs, UI and stress-testing, as an integrated member of an agile R&D team, building a robust application.
Take responsibility for the quality delivery of product releases.
Participate in defining and optimizing the R&D work processes.

DRS RADA is a global pioneer of radar systems for active military protection, counter-drone applications, critical infrastructure protection, and border surveillance. Join Our Team as a Project System Engineer at DRS RADA Technologies! DRS RADA Technologies is seeking a talented individual to join our team and contribute to the development of advanced radar-based electronic systems. About the job:
* Lead the development of advanced radar-based electronic systems
* Act as the primary point of contact for technical matters
* Collaborate with the R&D, engineering, and product teams to ensure timely delivery