דרושים » הנדסה » AI Architect - Platform Infrastructure (Gen AI application team)

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.

We are seeking for an experienced, hands-on Senior ML / AI Engineer to join the Generative AI applications platform group at our company and lead the implementation and integration of AI/ML solutions.
As a Senior ML / AI Engineer at our company you will...
Understand the challenges our users face and how to integrate and implement AI/ML solutions to solve those challenges
Work with stakeholders such as engineers, Product Management, and analysts to translate business problems to technical requirements and solutions
Design, develop, and implement POCs for ML models and GenAI solutions to address business needs and objectives
Provide technical guidance and mentorship to development teams on AI/ML technologies and practices
Build ML capabilities from ideation to production.

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.

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 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

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 seek a Lead AI Engineer specializing in prompt engineering and optimizing large language models (LLMs) for real-world applications. In this role, you will not only design effective prompts, improve model responses, and build AI agents, but also take the lead in shaping and delivering the initial AI-powered product for the company. You'll be responsible for driving the technical vision, building from scratch, and leading the implementation of AI-driven capabilities that will become a core part of our product offering.
Responsibilities:
Prompt Engineering: Develop, test, and optimize prompts for high-quality AI responses across different tasks.
Retrieval-Augmented Generation (RAG): Implement RAG-based solutions to improve AI responses using external knowledge bases.
Integration & API Development: Work with software engineers to embed AI features into our product via APIs.
AI Agent Development: Design, build, and deploy autonomous AI agents that can reason, and execute multi-step tasks using LLMs, tools, memory, and APIs.
Experimentation & Evaluation: Continuously refine models using A/B testing, human feedback loops, and AI evaluation metrics.
Stay Updated: Keep up with the latest LLM advancements and best practices in the AI industry.
Product applications: Apply LLMs and agents to real-world scenarios that solve meaningful user problems.
Product implementation: Work closely with the product team to secure delivery is aligned with expected product requirements
Response validation: Implement a process to ensure accurate KPI measurement and consistent, expected outcomes.

We are looking for an experienced AI/ML Engineer to join our Applications team within our platform engineering group. In this role, you'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and ML pipelines. You'll translate cutting-edge data science research into practical, scalable solutions, handling model deployment both in cloud environments and on-premises using GPUs and CUDA. Youll optimize and implement ML models, workflows, and AI agents to ensure high performance and reliability in production environments.
Responsibilities:
Design, implement, and deploy ML models, AI-driven applications, AI workflows, and LLM-based agents into production.
Build, manage, and maintain robust ML pipelines and systems.
Deploy models on cloud and on-premises GPU servers.
Optimize system performance, including model inference, scalability, and resource utilization both on cloud and on-premises.
Develop and maintain services, APIs and integrate ML models into microservices-based applications.
Collaborate with cross-functional teams including data science, backend, DevOps, and platform teams.
Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.

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 searching for a passionate and experienced hands-on AI Architect to join our team.

With a wide array of responsibilities and corresponding impact, youll help spearhead our product offering and wear multiple hats at a fast-growing, dynamic, early-stage company.

Responsibilities
Design, develop, and drive design processes and products that incorporate Generative AI (LLMs), models and knowledge Retrieval in order to help patients across the US.
Design and define data pipelines and evaluation pipelines.
Coach teams on best practices for datasets and building data sets.
Build applicative AI in production on a large scale.
Build solutions for different mediums including voice products with minimal latency and high accuracy.
Build an internal tool system to allow scientific evaluation.
Implement and lead new AI strategies by designing and implementing complex functionality and/or integrating with 3rd parties.
Continuously improve our existing NLP capabilities to help patients across the US answer any question, schedule appointments with their doctor, refill their prescriptions, and much more.
Use best practices and SOTA from the AI industry but also push the envelope to new heights.