דרושים » AI » AI Systems Engineer

we are looking for an AI Platform Engineer to revolutionize engineering productivity and drive AI-powered innovation across the organization. This role is part of our Platform Engineering initiative, focused on enabling engineers and product teams with cutting-edge AI tools, automation, and scalable AI platforms.
If youre an innovator at heart, passionate about leveraging AI to solve complex problems, and thrive in an environment where experimentation and entrepreneurship are encouragedthis role is for you.
Responsibilities:
 Develop and integrate AI-powered solutions to enhance engineering productivity, automate workflows, and improve developer efficiency.
Evaluate and implement state-of-the-art AI platforms (ChatGPT, Claude, Gemini, custom models) to solve engineering and operational challenges.
Design and maintain AI-driven internal platforms such as knowledge management systems, AI-enhanced coding assistants, intelligent automation tools, and AI-powered chatbots.
Work alongside engineering, DevOps, and product teams to embed AI into everyday development workflows.
Lead Proof-of-Concept (PoC) projects, experimenting with LLMs, generative AI, and automation frameworks to create tangible business impact.
Stay ahead of emerging AI trends, researching and implementing cutting-edge AI models and tools.
Build scalable AI infrastructure that integrates with cloud environments (AWS, GCP, Azure) and engineering toolchains.
Promote a culture of innovation, empowering teams to embrace AI-driven solutions and fostering AI adoption across the organization.

As a Big Data & GenAI Engineering Lead within our company's Data & AI Department, you will play a pivotal role in building the data and AI backbone that empowers product innovation and intelligent business decisions. You will lead the design and implementation of our companys next-generation lakehouse architecture, real-time data infrastructure, and GenAI-enriched solutions, helping drive automation, insights, and personalization at scale. In this role, you will architect and optimize our modern data platform while also integrating and operationalizing Generative AI models to support go-to-market use cases. This includes embedding LLMs and vector search into core data workflows, establishing secure and scalable RAG pipelines, and partnering cross-functionally to deliver impactful AI applications.
As a Big Data & GenAI Engineering Lead in our company you will...
Design, lead, and evolve our companys petabyte-scale Lakehouse and modern data platform to meet performance, scalability, privacy, and extensibility goals.
Architect and implement GenAI-powered data solutions, including retrieval-augmented generation (RAG), semantic search, and LLM orchestration frameworks tailored to business and developer use cases.
Partner with product, engineering, and business stakeholders to identify and develop AI-first use cases, such as intelligent assistants, code insights, anomaly detection, and generative reporting.
Integrate open-source and commercial LLMs securely into data products using frameworks such as LangChain, or similar, to augment AI capabilities into data products.
Collaborate closely with engineering teams to drive instrumentation, telemetry capture, and high-quality data pipelines that feed both analytics and GenAI applications.
Provide technical leadership and mentorship to a cross-functional team of data and ML engineers, ensuring adherence to best practices in data and AI engineering.
Lead tool evaluation, architectural PoCs, and decisions on foundational AI/ML tooling (e.g., vector databases, feature stores, orchestration platforms).
Foster platform adoption through enablement resources, shared assets, and developer-facing APIs and SDKs for accessing GenAI capabilities.

Were hiring a Machine Learning Engineer to accelerate AI-driven innovation across our B2B SaaS product and the broader organization.
This is a hands-on, end-to-end development role where you'll lead the implementation of ML/LLM-based solutions that boost operational efficiency and deliver exceptional product experiences. As an AI-First company, we embed AI across every department and workflowyou'll be at the heart of this transformation.
You will collaborate closely with product managers, engineers, and stakeholders to identify impactful AI opportunities, build state-of-the-art systems, and scale them across the organization.
What You Will Do:
AI-First Development: Design and implement POCs and production-ready ML/LLM solutions that address real-world business problems.
End-to-End Execution: Own projects from research through deployment, including model training, evaluation, integration, and monitoring.
Tool Evaluation: Stay current with state-of-the-art ML/LLM tools and frameworks (e.g., LangChain, Hugging Face Transformers, TensorFlow, PyTorch) and recommend their application.
Collaboration: Partner with engineering, product, and operations teams to embed AI into user-facing features and internal workflows.
System Integration: Build scalable microservices and APIs to deliver AI capabilities across the product.
Operationalization: Contribute to DevOps practices for CI/CD, observability, and ongoing optimization of AI models.
Strategic Reporting: Communicate progress and insights directly to senior management.

Were looking for a Generative AI Developer to join our forward-thinking engineering team. This role is perfect for someone with a passion for cutting-edge AI, a strong software engineering background, and the creative spark to identify and implement novel use cases within our product.

You will play a critical role in adding AI capabilities to our FinOps SaaS platform. Whether it's enhancing user workflows, automating insights, or inventing entirely new product experiences, youll have both the freedom and support to experiment and execute.

provides a uniquely rich dataset covering the full scope of a companys cloud spend. This expansive data playground offers a powerful foundation for experimentation and insight generation, enabling the development of intelligent, value-driven features.

Responsibilities
Design, build, and deploy generative AI-powered features across our product.
Identify opportunities for AI integration by proactively exploring FinOps use cases and user needs
Prototype and validate new AI use cases quickly and iterate based on internal and external feedback
Collaborate cross-functionally with product, design, and backend teams to drive innovation from concept to production
Stay current with the fast-moving generative AI landscape and evaluate new models, APIs, and tools (e.g., OpenAI, Anthropic, Hugging Face, AWS Bedrock, open-source LLMs).
Live in the future and track new innovations and paradigms in this fast-evolving field, and identify opportunities to integrate them into the product
Implement safeguards, prompt engineering techniques, and usage monitoring to ensure high-quality AI outputs
Optimize model performance, inference time, and cost efficiency within AWS infrastructure

were looking for an AI Product Specialist. In this individual-contributor role, you'll design and build production-ready AI agents, shape our prompt strategy, and ensure every customer-facing team can confidently demo and customize the Builder.

Youll spend approximately 60% of your time on hands-on agent building and prompt engineering, 30% on outbound enablement and GTM support, and 10% on special initiatives such as internal hackathons.

Responsibilities

Own the end-to-end design and development (mostly vibe-coding) of AI agents on our Builder platform, coordinating with stakeholders and ensuring clear, timely communication throughout the process.
Craft, test, and iterate prompts; establish reusable templates and guardrails to ensure the best user experience, trust, and consistent brand voice.
Collaborate closely with customer-facing teams to refine customer-tailored prompts and continuously improve product experience.
Identify new agent opportunities through market research, customer interviews, and field feedback; translate insights into a prioritized backlog.
Enable customer-facing teams (Solutions Engineering, CSM, Sales), Product, and Engineering teams with demo environments, playbooks, decks, and demo-in-a-box kits; run live enablement sessions and certification programs.
Track adoption KPIs of the AI Buildertraining completion, agent usageand present monthly scorecards to leadership.
Lead special initiatives, such as internal hackathons, to spark innovation and develop new production agents.
Serve as the primary subject-matter expert for advanced AI Builder questions, troubleshoot issues, and gather feedback for the product roadmap.

We are seeking a Staff Engineer for our AI Incubation team.
This role reports to the Chief Scientist and is a key member of a new team responsible for leveraging our extensive dataset of customer interactions to develop and validate new product capabilities.
The primary responsibility of this role is to rapidly prototype and test new Generative AI concepts, demonstrating a strong entrepreneurial spirit by transforming nascent ideas into tangible proofs-of-concept with speed and agility. Working closely with a Data Scientist, you will translate ideas from customers and internal stakeholders into functional proofs-of-concept to evaluate their technical feasibility and business potential. This role requires a self-starter who thrives on building from the ground up, embracing the challenge of bringing innovative AI solutions to life from initial concept.
Responsibilities:
Prototyping: Design, build, and deploy functional prototypes for new Generative AI features, utilizing production data sources to demonstrate technical feasibility.
Architectural Design: For validated prototypes, create high-level architectural designs and documentation to guide production implementation by core engineering teams. Ensure designs account for scalability, reliability, and security requirements.
Technology Evaluation: Evaluate emerging Generative AI technologies, including new models, frameworks, and architectural patterns (e.g. agentic frameworks, MCPs). Assess their applicability to our product and technical environment.
Collaboration: Collaborate with data scientists, product managers, and engineers throughout the prototyping lifecycle. Participate in technical discussions with customers and internal stakeholders to refine requirements.
Technical Guidance: Provide technical guidance to ensure that proposed AI features are aligned with engineering best practices, data constraints, and architectural standards.

Were looking for a Product Manager to lead our companys LLM Infrastructure - a foundational role driving the development of systems that enable smarter, AI-powered decision making across the marketplace.
As the PM for LLM Infrastructure, youll shape the capabilities that turn unstructured data into structured, explainable, and actionable insights. Youll work closely with ML engineers, data scientists, and product leaders to design scalable tools and frameworks that support use cases across personalization, matching, search understanding, trust and safety, and more.
Your mission will be to build reliable and extensible LLM-based systems that serve as core building blocks for future-facing product innovation.
What am I going to do?
Define the product vision and roadmap for our companys LLM infrastructure, aligning with long-term company strategy and cross-team needs.
Lead the development of scalable systems that extract meaning and structure from conversational and behavioral data.
Drive adoption of LLM capabilities across our company by building unified APIs, shared frameworks, and streamlined integration pipelines.
Partner with engineering, data science, and research teams to deliver high-quality infrastructure that powers AI-native product experiences.
Collaborate on system design and architecture decisions to ensure alignment between technical solutions and product scope.
Ensure reliability, scalability, explainability, and performance in all LLM-based systems.
Manage technical complexity and connect infrastructure efforts with clear business value.

If you share our love of sports and tech, you've got the passion and will to better the sports-tech and data industries - join the team. We are looking for a Data & AI Architect.
Responsibilities:
Build the foundations of modern data architecture, supporting real-time, high-scale (Big Data) sports data pipelines and ML/AI use cases, including Generative AI.
Map the companys data needs and lead the selection and implementation of key technologies across the stack: data lakes (e.g., Iceberg), databases, ETL/ELT tools, orchestrators, data quality and observability frameworks, and statistical/ML tools.
Design and build a cloud-native, cost-efficient, and scalable data infrastructure from scratch, capable of supporting rapid growth, high concurrency, and low-latency SLAs (e.g., 1-second delivery).
Lead design reviews and provide architectural guidance for all data solutions, including data engineering, analytics, and ML/data science workflows.
Set high standards for data quality, integrity, and observability. Design and implement processes and tools to monitor and proactively address issues like missing events, data delays, or integrity failures.
Collaborate cross-functionally with other architects, R&D, product, and innovation teams to ensure alignment between infrastructure, product goals, and real-world constraints.
Mentor engineers and promote best practices around data modeling, storage, streaming, and observability.
Stay up-to-date with industry trends, evaluate emerging data technologies, and lead POCs to assess new tools and frameworks especially in the domains of Big Data architecture, ML infrastructure, and Generative AI platforms.

We are seeking an experienced Data Scientist with a strong background in AI engineering to join our AI Platform team. This role focuses on developing and fine-tuning advanced machine learning models, including LLMs, to support various product teams across our company. As a member of the AI Platform team, you will collaborate with cross-functional teams to build scalable, efficient, and robust AI solutions that serve diverse business domains.
What am I going to do?
Take leading roles in foundational AI projects across our company: developing and fine-tuning LLMs, building reusable components for generative AI, supporting real-time predictions, and enabling streaming data utilization across online models.
Provide advanced Data Science and AI Engineering solutions end-to-end - from research and prototyping to robust production-grade implementations.
Own the design, training, and evaluation of models tailored for tasks like summarization, classification, semantic matching, personalization, and more.
Drive innovation by exploring new model architectures, training techniques, and fine-tuning strategies aligned with business needs.
Lead and mentor other team members, setting high standards for technical excellence and knowledge sharing.
Continuously identify new opportunities to evolve the platforms capabilities and streamline how AI is built and adopted across our company.

Were seeking a visionary and technically hands-on AI Lead to join us and take charge of driving innovation across our core AI systems. As the AI Lead, you'll guide the architecture and development of advanced machine learning models that power our video and creative analysis platform. You will collaborate cross-functionally with product managers, engineering, and business development teams to deliver cutting-edge features that push the boundaries of whats possible in creative performance analysis.
This is a high-impact role for someone who thrives at the intersection of machine learning, product strategy, and creativity.
Key Responsibilities:
Lead the development, deployment, and optimization of machine learning models for video, image, and creative performance analysis.
Architect scalable AI/ML pipelines and infrastructure that support real-time and batch processing of multimedia data.
Guide research and experimentation initiativesidentify new technologies, modeling techniques, and opportunities for innovation.
Mentor and grow a team of machine learning engineers and data scientists as we scale.
Champion AI ethics, fairness, and explainability in our model development and deployment.
Stay ahead of industry trends in generative AI, computer vision, NLP, and Martech innovation, translating insights into competitive advantages.