דרושים » תוכנה » AI Lead

We are looking for a passionate and experienced Hands-On Tech Lead to join our Technology Consulting department and lead the design and implementation of cutting-edge Generative AI solutions. This role is ideal for someone who thrives at the intersection of technology leadership and hands-on development, and who is excited to shape the future of AI-driven innovation for top-tier clients.
Key Responsibilities:
Lead the technical design, architecture, and implementation of Generative AI solutions (e.g., LLMs, multimodal models, RAG pipelines, fine-tuning, prompt engineering).
Collaborate with cross-functional teams including data scientists, software engineers, consultants, and business stakeholders.
Stay up to date with the latest advancements in GenAI and translate them into practical, scalable solutions.
Guide and mentor junior developers and AI engineers.
Work closely with clients to understand business needs and translate them into technical requirements.
Ensure high-quality delivery, performance, and security of AI applications.

We are looking for an exceptional MLOps Team Lead to own, build, and scale the infrastructure and automation that powers state-of-the-art Large Language Models (LLMs) and AI systems.
This is a technical leadership role that blends hands-on engineering with strategic vision. You will define MLOps best practices, build high-performance ML infrastructure, and lead a world-class team working at the intersection of AI research and production-grade ML systems.
You will work closely with LLM Algorithm Researchers, ML Engineers, and Data Scientists to enable fast, scalable, and reliable ML workflows covering everything from distributed training to real-time inference optimization.
If you have deep technical expertise, thrive in high-scale AI environments, and want to lead the next generation of MLOps, we want to hear from you.

We are looking for an experienced Software Engineer with GenAI/ML knowledge to join our AI/ML Applications team. In this role, you'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and GenAI pipelines. You'll translate cutting-edge data science research into practical, scalable solutions, handling model/agent deployment both in cloud environments and on-premise. Youll optimize and implement workflows, and AI agents to ensure high performance and reliability in production environments.

Responsibilities
Design, implement, and deploy AI-driven applications, AI workflows, and LLM-based agents into production.
Build, manage, and maintain robust GenAI systems.
Optimize system performance, including robustness, scalability, communication protocols 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 and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.

We are seeking a Senior Software Architect to lead and shape the architectural vision of our SaaS healthcare platform, guide the adoption of cutting-edge AI technologies, and ensure our solutions remain scalable, secure, and future-ready.
This is a hands-on, strategic leadership role that combines visionary system design, proof-of-concept development, and AI-first innovation enablement.
Responsibilities:
1. Architectural Leadership
Define, communicate, and evolve the platforms architectural vision to ensure alignment with business goals.
Lead high-level design discussions and decisions for new and existing products.
Establish and maintain architectural principles, standards, and patterns across all engineering teams to ensure consistency and coherence.
Drive cloud-native architecture in AWS with a strong focus on scalability, availability, performance, and cost efficiency.
2. Innovation & Emerging Technology
Build POCs and pilots for new solutions, frameworks, and AI capabilities.
Evaluate emerging trends in AI, LLMs, MCPs, agents, and developer productivity tools, ensuring strategic adoption where relevant.
Initiate projects/features to solve widespread problems (including work with Support, DevOps, Infosec)
3. AI Tooling Evangelism
Spearhead engineering-wide adoption of AI-assisted development workflows, including developer productivity tools, code copilots, automated quality checks, and automated documentation.
Define best practices, guidelines, and governance for AI usage in development (e.g., Cursor configuration rules, prompt engineering standards).
Educate and mentor teams on effective AI utilization for engineering, product, and operational tasks, taking into account security, costs, and compliance.
4. Technical Governance & Best Practices
Overall ownership of the system scalability, COGS, and stability of the Navina product(s)
Define standards for coding, testing, CI/CD, and monitoring.
Enforce architectural and design reviews for key initiatives.
5. Cross-functional Collaboration
Work closely with Engineering, Product, Data Science, DevOps, and Security teams to deliver well-architected solutions.
Communicate complex technical concepts to non-technical audiences, including executives and external partners.

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 looking for a passionate Computer Vision Software Team Leader who is excited to create, shape, and influence our products and company vision. As a Team Leader, youll deliver scalable, high-quality infrastructure that integrates AI models with complex application needs.
You will build fast, reliable, and efficient solutions on edge devices, as well as machine learning cloud-based systems and pipelines.
You will tackle technological challenges in performance and data scale, and uphold high standards for code quality and architecture.
Youll need both low-level and high-level expertise to address performance and AI challenges, while delivering robust features and infrastructure. You will continuously improve development processes, adopt new technologies, and help shape the future of retail through world-class AI solutions.
About The Role:
Lead the teams day-to-day activities, effectively managing priorities and navigating technical and organizational challenges.
Plan and coordinate work based on business goals estimate effort, set realistic timelines, and ensure timely delivery of high-quality results.
Design, develop, and deliver the next generation of features for our AI-driven solutions.
Conduct code and design reviews, evaluate implementations, and provide clear, constructive technical feedback.
Build and grow a high-performing team recruit, coach, mentor, and empower engineers to reach their full potential.
Collaborate cross-functionally with other teams to define and deliver features and initiatives that span across departments.
Foster a strong engineering culture by promoting best practices, high standards, and continuous improvement.

we are looking for a Senior Data Engineer
What You'll Do:

Shape the Future of Data - Join our mission to build the foundational pipelines and tools that power measurement, insights, and decision-making across our product, analytics, and leadership teams.
Develop the Platform Infrastructure - Build the core infrastructure that powers our data ecosystem including the Kafka events-system, DDL management with Terraform, internal data APIs on top of Databricks, and custom admin tools (e.g. Django-based interfaces).
Build Real-time Analytical Applications - Develop internal web applications to provide real-time visibility into platform behavior, operational metrics, and business KPIs integrating data engineering with user-facing insights.
Solve Meaningful Problems with the Right Tools - Tackle complex data challenges using modern technologies such as Spark, Kafka, Databricks, AWS, Airflow, and Python. Think creatively to make the hard things simple.
Own It End-to-End - Design, build, and scale our high-quality data platform by developing reliable and efficient data pipelines. Take ownership from concept to production and long-term maintenance.
Collaborate Cross-Functionally - Partner closely with backend engineers, data analysts, and data scientists to drive initiatives from both a platform and business perspective. Help translate ideas into robust data solutions.
Optimize for Analytics and Action - Design and deliver datasets in the right shape, location, and format to maximize usability and impact - whether thats through lakehouse tables, real-time streams, or analytics-optimized storage.
You will report to the Data Engineering Team Lead and help shape a culture of technical excellence, ownership, and impact.

We are looking for a Senior Data Engineer.
As a Senior Data Engineer, youll be more than just a coder - youll be the architect of our data ecosystem. Were looking for someone who can design scalable, future-proof data pipelines and connect the dots between DevOps, backend engineers, data scientists, and analysts.
Youll lead the design, build, and optimization of our data infrastructure, from real-time ingestion to supporting machine learning operations. Every choice you make will be data-driven and cost-conscious, ensuring efficiency and impact across the company.
Beyond engineering, youll be a strategic partner and problem-solver, sometimes diving into advanced analysis or data science tasks. Your work will directly shape how we deliver innovative solutions and support our growth at scale.
Responsibilities:
Design and Build Data Pipelines: Architect, build, and maintain our end-to-end data pipeline infrastructure to ensure it is scalable, reliable, and efficient.
Optimize Data Infrastructure: Manage and improve the performance and cost-effectiveness of our data systems, with a specific focus on optimizing pipelines and usage within our Snowflake data warehouse. This includes implementing FinOps best practices to monitor, analyze, and control our data-related cloud costs.
Enable Machine Learning Operations (MLOps): Develop the foundational infrastructure to streamline the deployment, management, and monitoring of our machine learning models.
Support Data Quality: Optimize ETL processes to handle large volumes of data while ensuring data quality and integrity across all our data sources.
Collaborate and Support: Work closely with data analysts and data scientists to support complex analysis, build robust data models, and contribute to the development of data governance policies.

We are seeking an AI Product Manager to lead the development and optimization of our AI agent platform. This is an individual-contributor role, ideal for a product leader with deep experience in AI-driven products and a passion for accessibility. You will own the end-to-end lifecycle of AI agents, from ideation through deployment, and play a pivotal role in shaping our AI strategy and customer enablement efforts. You will be managed by the Product Team Lead.

Youll spend approximately 40% of your time on hands-on agent building and prompt engineering, 30% on outbound enablement and go-to-market support, and 30% on special initiatives such as internal innovation initiatives.

What will you do:

Own the full-cycle design, development (with a strong emphasis on vibe coding and other advanced agent techniques), and launch of AI agents on our platform, ensuring stakeholder alignment and clear communication throughout.
Develop, test, and iterate on prompts; establish reusable templates and robust guardrails to ensure optimal user experience, trust, and consistent brand voice.
Collaborate closely with customer-facing teams to refine and tailor AI agent prompts, continuously improving product experience for diverse accessibility needs.
Identify new AI agent opportunities through market research, customer interviews, and field feedback; translate insights into a prioritized product backlog.
Enable internal teams (Solutions Engineering, Customer Success, Sales), Product, and Engineering with demo environments, playbooks, and decks; lead live enablement sessions and certification programs.
Track adoption KPIs for the AI platformmonitoring training completion, agent usage, and presenting monthly scorecards to leadership.
Lead special initiatives, such as internal hackathons or innovation initiatives, to drive new agent development and foster a culture of experimentation.
Serve as a subject-matter expert for advanced AI agent questions, troubleshoot issues, and gather feedback for the product roadmap.

We're looking for talented, versatile and highly independent Machine Learning Engineers to join our winning team. You will be in charge of end-to-end development and you'll have a massive impact on the product and the technical decisions made.
The ML Engineers are part of our infrastructure group, working closely with the exceptional research team, taking trained models and scaling them out to production.
Responsibilities:
Take ownership of the entire machine learning engineering lifecycle - from building scalable training and evaluation pipelines to deploying models in production, with robust monitoring and maintenance systems.
Help in creating scalable solutions by enabling us to continuously increase the accuracy of our algorithms across thousands of clinics.
Designing a secured large-scale system that is suitable for sensitive patient data.
Continue to enhancing our deep learning infrastructure to supports our AI models at scale, including CI/CD, automation, testing and monitoring.
Collaborate with the research, medical and product teams in implementing ML solutions to the digital health space.