דרושים » הנדסה » AI Incubation Staff Engineer

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

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.

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.

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.

Were looking for a Principal Software Engineer with a builders mindset and a passion for innovation to join our AI Security team at BigID.
Youll play a key role in shaping how organizations adapt and secure their use of AI, working on new initiatives from the ground up. The ideal candidate is a hands-on technical leader who thrives in ambiguity, brings deep backend expertise, and influences cross-team architecture and product direction.
This is a unique opportunity to work on cutting-edge AI Security initiatives in a fast-paced, high-ownership environment.
What Youll Do:
Design scalable, secure solutions to complex technical challenges
Build backend services and infrastructure from the ground up
Drive architectural and technological decisions across products
Collaborate closely with cross-functional teams and mentor engineers
Review design and code to uphold high engineering standards
Explore new technologies and bring innovative ideas into production

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.

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 a talented Software Development Leader with a strong background in Large Language Models (LLM) and GenAI engineering.
This is a unique opportunity to work with our US clients and engage in global projects, leveraging your extensive skills in generative AI tools.
As a pivotal member of our team, you will be responsible for translating complex business problems into data-driven solutions, drafting methodologies, and executing innovative projects. In this role you will:
Lead development of robust, efficient, and scalable Python code, ensuring adherence to best practices in software engineering and optimization for high-performance applications.
Utilize GenAI engineering tools such as LangChain, RAG, Agents, and Vector Database for implementation and optimization.
Stay updated with AI protocols and standards and ensure their correct application in projects.
Collaborate with other teams and team members to understand requirements and develop solutions.
Analyze complex problems, identify and define the computational requirements to solve them.

founded by the team that invented one of the technologies at the heart of 5G. Their next vision was to develop an IoT sticker, a computing element that can power itself by harvesting radio frequency energy, bringing connectivity and intelligence to everyday products and packaging, things previously disconnect from the IoT. This revolutionary mixture of cloud and semiconductor technology is being used by some of the worlds largest consumer, retail, food and pharmaceutical companies to change the way we make, distribute, sell, use and recycle products.

Our investors include Softbank, Amazon, Alibaba, Verizon, NTT DoCoMo, Qualcomm and PepsiCo.
We seek an experienced individual contributor (IC) with potential for future team leadership, specializing in deploying generative AI applications in production at scale. The role focuses heavily on robust production methodologies, including monitoring, evaluation, failure analysis, and resilience.

Reporting to the Director, you'll shape Wiliots AI roadmap for internal tools, customer solutions, and external SDKs.

Responsibilities
Develop, deploy, and scale robust generative AI applications (agents, copilots, intelligent interfaces).
Design and maintain scalable, secure architectures for LLM-driven services.
Own full AI lifecycle: prompt engineering, embedding models, retrieval systems (vector DBs), real-time monitoring, observability, and failure mitigation.
Collaborate cross-functionally with software engineers, product teams, and business stakeholders.
Translate ambient IoT data into practical AI-driven experiences (logistics, sustainability, inventory management).
Contribute to developing SDKs/APIs for external AI workflows.
Experiment with advanced GenAI techniques (LLMs, hybrid search, multimodal).

In this role, you will lead a team of Machine Learning Scientists and Engineers dedicated to building, training, and deploying cutting-edge Generative AI models. This includes developing foundation models trained on extensive textual data and creating fine-tuned models designed to tackle complex travel-related tasks. Your leadership will play a pivotal role in advancing the application of AI to transform the travel experience for millions of customers.
As a technical manager, you should be passionate about GenAI technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML roadmap, and not be afraid to get your hands dirty with code when needed.

You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.

When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.

Key Job Responsibilities and Duties:
Leadership in LLM Development- Build, Guide and mentor a team of ML scientists and ML engineers in the development, fine-tuning, and deployment of large language models (LLMs) tailored for the travel domain.
Expertise in the engineering aspects of deploying LLMs at scale with minimal latency. This includes optimizing model performance, scalability, and efficiency to meet the demands of real-time, high-traffic applications.
Define and communicate the technical vision and strategy for LLM-related initiatives, ensuring alignment with company goals and customer needs.
Foster a culture of collaboration, innovation, and excellence within the team.
Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times.
Translate machine learning vision and strategy into planning and execution, and ensure timely delivery of their plans.
Develop innovative ML models, algorithms, and engineering approaches or identify existing ones, with the potential to impact our business.
Design and execute applied research plans to understand, apply, test, evolve, and generalize these technologies into reusable frameworks.
Translate business problems into viable, reliable and robust ML and AI solutions, accounting for constraints of the production environment.
Monitor product health, performance and business impact and act accordingly when requirements are not met.
Identify underlying issues and opportunities across domains and situations that are not obviously related through application of structured thinking and logic.