דרושים » תוכנה » Generative AI Engineer

The Ecosystems Engineering group is seeking a Principal Software Engineer to join our rapidly growing team. This is a game-changing opportunity to join an open-source AI platform that harnesses the power of hybrid cloud to drive innovation. In this role, you will work with a diverse team of highly talented engineers on designing, implementing, and productizing new AI solutions, with a focus on deep integration of the AI stack, hardware accelerators, and leading OEMs and Cloud Computing Service Providers (CCSPs).

You'll play a critical role in shaping the next generation of hybrid cloud platforms by directly contributing to our innovative AI and Edge products. This is your chance to be at the forefront of AI's exciting evolution, joining an ecosystem that champions continuous learning, career growth, and professional development. You'll also collaborate closely with product management, other engineering teams, and key partners and lighthouse customers.

What You Will Do:

Architect and lead the implementation of new features and solutions for our AI and Edge products.

Explore deep code integration into various products, ensuring optimal integration between the company`s portfolio, hardware accelerators and partners.

Provide technical vision and leadership on critical and high-impact projects, ensuring non-functional requirements including security, resiliency, and maintainability are met.

Integrate software that leverages hardware accelerators (e.g., DPUs, GPUs, AIUs) and perform performance analysis and optimization of AI workloads with accelerators.

Work with major AI and hardware partners such as NVIDIA, AMD, Dell, and others on building joint integrations and products.

Collaborate closely with UX, UI, QE, and cross-functional teams to deliver a great experience to our partners and customers.

Coordinate with team leads, architects, and other engineers on the design and architecture of our offerings.

Become responsible for the quality of our offerings, participate in peer code reviews and continuous integration (CI), and respond to security threats.

Mentor, influence, and coach a distributed team of engineers, contributing to a culture of continuous improvement by sharing recommendations and technical knowledge.

We are seeking a motivated and hands-on IT Software Engineer with 25 years of proven experience in AI development. As part of our IT development team, you will design, build, and deploy AI-powered applications and solutions that drive innovation and improve business productivity. You will work closely with software engineers, business analysts, and business stakeholders to implement AI models, agents, and copilots using modern tools and platforms.
This is a great opportunity for someone passionate about AI, who enjoys building practical solutions and growing their expertise in enterprise-scale environments.
How will you make an impact?
Be an active member of the IT development team, contributing to design, coding, and deployment of AI-driven solutions.
Develop and implement AI agents, copilots, and automation workflows using tools such as Microsoft Copilot Studio, Azure OpenAI, Azure AI Foundry, and Python.
Integrate AI models and components into existing applications, systems, and business processes.
Write clean, maintainable, and efficient code for AI-driven features and applications.
Apply prompt engineering techniques to optimize large language model (LLM) performance.
Collaborate with cross-functional teams (data engineering, product, business) to translate requirements into working AI solutions.
Participate in code reviews, testing, debugging, and deployment of AI applications.
Stay up to date with emerging AI technologies and contribute ideas for their adoption.
Support the monitoring and maintenance of AI models in production, including performance tuning and troubleshooting.

Join the forefront of AI and Cybersecurity.
we are seeking an experienced and visionary Product Manager to lead the strategy, roadmap, and delivery of cutting-edge LLM security solutions. This isnt just about managing a product its about helping define a new category of security in the AI era.
If youre passionate about AI, skilled at building security products, and thrive at the intersection of innovation and protection, this role is for you.
Responsibilities:
Define and own the vision, strategy, and roadmap for LLM Security products.
Partner with engineering, data science, and threat research to deliver high-impact features that secure AI applications, copilots, and models.
Engage directly with customers, analysts, and industry leaders to validate product direction and uncover unmet needs.
Translate customer pain points, compliance requirements, and threat intelligence into actionable product capabilities.
Drive full end-to-end product developmentfrom ideation and design to launch and iteration.
Stay ahead of the curve on LLM technologies and evolving attack techniques (e.g., prompt injection, data leakage, model abuse).
Evangelize product vision to executives, customers, and the broader market.

We are looking for an experienced backend engineer with a background in writing resilient and robust production services. Youre familiar with modern microservices architecture, technologies, and best practices. You have a strong problem-solving attitude and a deep sense of accountability, you are a team player, independent, and most importantly - youre passionate about what you do and about making things better.
We develop event-driven systems and real-time APIs that are used widely across and written mostly in Node.js, Go, and Python. Some of the technologies we work with include: Apache Kafka, K8S, managed AWS services (RDS, CloudFront, Athena, ElastiCache, etc), DataDog, and GraphQL.
What you'll do:
Develop end-to-end services and features, from gathering requirements and research to implementation, deployment, and monitoring.
Integrate and implement AI flows and solutions into the team and department.
Improve quality and find weaknesses in existing processes and services.
Participate in brainstorming and early-stage designs.
Mentor, advise, and work collaboratively within the group, with other development teams, and with all other business teams in the company.
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible.

The Senior Machine Learning Engineer GenAI is responsible for designing, implementing, and operating large-scale systems and tools for AI model benchmarking, optimization, and validation. Unlike a traditional ML Engineer focused primarily on model training, this role centers on building the infrastructure, automation, and services that enable systematic evaluation and performance tuning of LLMs at scale.

This position combines deep understanding of model serving frameworks, GPU optimization, and benchmarking methodologies with strong software engineering skills to deliver reliable, reproducible, and production-grade evaluation pipelines. The engineer will design and maintain validation-as-a-service platforms that allow internal and external stakeholders to assess models across latency, throughput, accuracy, and cost dimensionsintegrating seamlessly with our AI ecosystem and industry-standard GenAI tooling.

A core aspect of this role is creating a robust, extensible benchmarking and validation framework capable of running across diverse inference engines, hardware configurations, and deployment environments, while providing actionable insights for model selection, optimization, and integration.

What you will do:
Benchmarking Platform Development: Design and implement scalable benchmarking pipelines for LLM performance measurement (latency, throughput, accuracy, cost) across multiple serving backends and hardware types.

Optimization Tooling: Build utilities and automation to profile, debug, and optimize inference performance (GPU utilization, memory footprint, CUDA kernels, parallelism strategies).

Validation-as-a-Service: Develop APIs and self-service platforms for model evaluation, enabling teams to run standardized benchmarks on demand.

Serving Integration: Integrate and operate high-performance serving frameworks (vLLM, TGI, LMDeploy, Triton) with cloud-native deployment patterns.

Dataset & Scenario Management: Create reproducible workflows for dataset preparation, augmentation, and scenario-based testing to ensure robust evaluation coverage.

Observability & Diagnostics: Implement real-time monitoring, logging, and metrics dashboards (Prometheus, Grafana) for benchmark and inference performance.

Cloud-Native Orchestration: Deploy and manage benchmarking workloads on Kubernetes (Helm, Argo CD, Argo Workflows) across AWS/GCP GPU clusters.

Integration with GenAI Tooling: Leverage Hugging Face Hub, OpenAI SDK, LangChain, LlamaIndex, and internal frameworks for streamlined evaluation workflows.

Performance Engineering: Identify bottlenecks, apply targeted optimizations, and document best practices for inference scalability.

Ecosystem Leadership: Track emerging frameworks, benchmarks, and optimization techniques to continuously improve the evaluation platform.

We are looking for a talented Algorithm Engineer to join our Cognitive AI team. In this role, you will design, build, and optimize LLM-based agents that power real-time problem solving. You will be hands-on in Python, research-driven, and passionate about creating intelligent, scalable AI solutions that make a real impact.
Responsibilities:
Design, develop, and optimize LLM-based agents for real-world production use cases.
Build intelligent agent frameworks that orchestrate reasoning across tools, APIs, and knowledge bases.
Deploy and maintain LLM applications in production, ensuring performance, scalability, and reliability.
Research new approaches in LLMs and agent architectures, and integrate cutting-edge techniques into production systems.
Collaborate with cross-functional teams (product, engineering, data) to translate business needs into AI solutions.
Continuously monitor and optimize deployed models, diagnosing and resolving bottlenecks.
Think creatively about complex problems and deliver technological Innovation

We are looking for a Software Engineer with Kubernetes and MLOps (Machine Learning Operations) experience to join our rapidly growing engineering team. Our focus is to create a platform, partner ecosystem, and community by which enterprise customers can solve problems to accelerate business success using AI. This is a very exciting opportunity to build and impact the next generation of hybrid cloud MLOps platforms, contribute to the development of the RHOAI product, participate in open source communities, and be at the forefront of the exciting evolution of AI. Youll join an ecosystem that fosters continuous learning, career growth, and professional development.

As a core developer for one of our OpenShift AI teams, you will have the opportunity to actively participate in one of our component teams as well as the affiliated open-source communities. You will work as part of an evolving development team to rapidly design, secure, build, test, and release new capabilities. The role is primarily an individual contributor who collaborates closely with other developers and cross-functional teams. You should have a passion for working in open-source communities and for developing solutions that integrate us, open-source, and partner technologies into a cohesive platform.

What you will do:

Architect and lead implementation of new features and solutions for RHOAI.

Innovate in the MLOps domain by participating in upstream communities.

Provide technical vision and leadership on critical and high impact projects.

Ensure non-functional requirements including security, resiliency, and maintainability are met.

Write unit and integration tests and work with quality engineers to ensure product quality.

Use CI/CD best practices to deliver solutions as productization efforts into RHOAI.

Contribute to a culture of continuous improvement by sharing recommendations and technical knowledge with team members.

Collaborate with product management, other engineering and cross-functional teams to analyze and clarify business requirements.

Communicate effectively to stakeholders and team members to ensure proper visibility of development efforts.

Give thoughtful and prompt code reviews.

Represent RHOAI in external engagements including industry events, customer meetings, and open source communities.

Mentor, influence, and coach a distributed team of engineers.

We are seeking a skilled ML Engineer to design, build, and deploy advanced ML solutions that drive analytics, anomaly detection, and data classification across enterprise-scale environments.
This role will focus on developing and optimizing models, including LLMs and prompt engineering pipelines, and ensuring seamless integration into production workflows spanning cloud-native, on-premises, and Databricks ecosystems.
Key Responsibilities :
Design, build, and deploy ML models for user behavior analytics, anomaly detection, and data classification across enterprise environments.
Collaborate with data scientists, software and data engineers to integrate ML models into production pipelines, cloud-native environments, on-premises, and Databricks workflows.
Develop, fine-tune, and evaluate LLMs and prompt engineering solutions for data classification, labeling, and threat analysis features.
Optimize models using techniques like distillation, quantization, and efficient data structures to boost performance and lower resource cost.
Build high-performance data inputs using embeddings, vector databases, and distributed training frameworks.
Manage model lifecycle and performance via MLOps best practices: monitoring, retraining, and deploying updates.
Partner with data scientists, cybersecurity researchers and product teams to evaluate and refine ML-driven capabilities.
Conduct experiments and benchmark results in fast-paced, data-intensive environments.

Our team, a vital part of the Telco Verification Pillar, is developing and operating a cutting-edge CI/CD service to empower our Testing Teams with enhanced automation capabilities. As a Principal Software Engineer specializing in Test Automation, CI/CD, and DevOps, you will be instrumental in ensuring the quality, reliability, and efficiency of this critical service. You will collaborate closely with cross-functional teams to design, implement, and maintain robust automated testing frameworks, continuous integration/continuous deployment pipelines, and best-in-class DevOps practices.

What you will do:

Design, implement, and manage end-to-end CI/CD pipelines to automate build, test, and deployment processes.

Foster seamless collaboration with development, QA, and operations teams to fully integrate testing and deployment workflows.

Proactively monitor and analyze test results, identify root causes of issues, and work collaboratively with development teams for timely resolution.

Develop and maintain highly scalable and resilient infrastructure as code (IaC) using tools like Ansible or similar industry-standard solutions.

Implement and manage containerization and orchestration solutions using Docker and Kubernetes, with OpenShift knowledge being a significant advantage.

Identify and address test coverage gaps within existing test pipelines, proposing and developing new automated tests in close collaboration with Functional Testing (FT), System Testing (ST), and Solution Lifecycle Management (SLCM) teams.

Ensure the highest standards of security, scalability, and reliability for all CI/CD and DevOps processes.

Continuously research and integrate industry best practices and emerging technologies in test automation, CI/CD, and DevOps.

Act as a mentor and provide technical guidance to junior engineers, fostering a culture of best practices and continuous learning.

Leverage AI-driven insights to optimize test execution, prioritize critical test cases, and reduce overall testing cycles.

Integrate AI/ML models into test automation frameworks to enhance test case generation, anomaly detection in test results, and intelligent defect prediction.