דרושים » תוכנה » קפסולה מגייסת Head of Technical Operations לסטרט-אפ גלובלי המפתחת פלטפורמת SaaS מבוססת AI

We are seeking an experienced, strategic Senior Product Manager to lead the discovery, definition, and delivery of impactful product initiatives across platform. You will own the product vision and roadmap for your domain, balancing customer needs, technical feasibility, and long-term business goals. This role requires exceptional product thinking, leadership, data-driven decision making, and close collaboration with engineering, design, and go-to-market teams to drive innovation in the CPS space.
Responsibilities:
As a Senior Product Manager, your impact will be:
Product Discovery & Delivery: Empower and guide the product and engineering teams to discover, design, and build viable solutions to complex problems that delight customers.
Lifecycle Ownership: Own the end-to-end product lifecycle from strategy to execution-converting high-level market feedback, AI capabilities, and technical requirements into successful, scalable releases.
Strategic Roadmap: Play a key role in driving the product roadmap planning and prioritization process, synthesizing diverse inputs into a clear, forward-looking product definition.
Go-To-Market Partnership: Partner closely with Sales, Marketing, and Customer Success to drive product adoption, enable global teams, and support strategic GTM efforts.
Cross-Functional Collaboration: Work across horizontal R&D teams to ensure scalable, unified, and cohesive platform delivery.

Were looking for a Data & Analytics Team Lead to manage and grow our data team and own the data layer behind our AI. Youll lead a team of data analysts responsible for neural-network model analysis, model performance tracking, customer-facing and internal BI. Youll act as both the people manager and the technical lead for the team, setting technical direction while staying hands-on.
Youll thrive in this role if youre passionate about turning data into better AI products, enjoy solving complex analytical problems, and like working at the intersection of Data, Analytics, and Artificial Intelligence.
Responsibilities:
Lead the data strategy supporting AI model development, evaluation, and continuous improvement
Define KPIs and monitoring frameworks for AI model performance.
Analyze NN model outputs, build and maintain model-tracking and performance-evaluation workflows
Drive close calibration with the Algo, Product, and Data Engineering teams to align data definitions, pipelines, and metrics
Stay hands-on with SQL, Python, BI tooling, and the modern data stack
Build and own agentic data workflows - designing the context, tooling, and data access that let AI agents reliably query, analyze, and act on company data

We're looking for a Machine Learning Team Lead to own real parts of it.
What you'll actually do?
Lead, mentor, and grow a multidisciplinary team composed of Data Scientists, Data Analysts, and DLP Analysts.
Define and lead the team's technical vision and execution strategy, driving technical excellence and ensuring alignment with business priorities and product objectives.
Oversee the design, development, validation, and deployment of advanced machine learning solutions for customer-facing products.
Hands-on ownership of current AI services.
Establish and enforce best practices for model development, experimentation, evaluation, documentation, and code quality.
Collaborate closely with Product Managers, Data Engineers, Software Engineers, and domain experts to translate business challenges into scalable ML solutions.
Drive execution and delivery, balancing innovation, technical quality, and time-to-market considerations.
Promote operational excellence by improving the reliability, scalability, and maintainability of production machine learning systems.
Establish scalable engineering processes, workflows, and best practices.
Lead the team transformation from an early-stage organisation into a mature, production-grade AI engineering team.

we are seeking an experienced and visionary ML Engineer to join our dynamic technology organization. The successful candidate will be a part of a team of talented AI Engineers, Building agentic AI solutions, driving innovation and delivering business value through advanced Generative AI solutions & machine learning techniques. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge Gen AI and LLM methodologies and a passion for continuous learning and development.

Responsibilities

Build the solution: Own end-to-end technical delivery of agentic systems, from source-system integration through agent design, development, evaluation, and production deployment.
Integrate AI systems with source systems (Salesforce, Databricks, Splunk, internal APIs, business applications). Handle agent harness and orchestration.
Handle the operational handover to the business function and any necessary support transition.
Collaborate across teams: Partner closely with data engineering, platform, security, and business teams to align on requirements, dependencies, and integration points.
Engage stakeholders: Gather requirements directly from business functions, communicate technical trade-offs clearly, and keep stakeholders informed on progress, risks, and timelines.
Uphold quality and reliability: Establish and maintain best practices for code quality, testing, evaluation, monitoring, and observability of deployed AI systems.
Contribute to the team's technical growth through knowledge-sharing and help shape engineering standards and reusable patterns.
Stay current: Continuously evaluate emerging Gen AI, LLM, and agentic frameworks, and recommend tools and approaches that improve delivery speed and solution quality.

we are seeking an experienced Director of Engineering to lead and scale our software, QA, DevOps, and IT groups in a leading AI startup. This role combines strong people leadership, ownership of execution, and deep technical understanding of production-grade systems.
You will manage engineering managers, drive delivery excellence, and ensure alignment between R&D strategy and business priorities.
Responsibilities:
Lead two engineering groups: IT & DevOps and Software & QA
Manage and develop engineering managers and team leads
Own execution, delivery, quality, and operational excellence across all engineering domains
Drive scalable engineering processes, methodologies, and best practices
Partner closely with Product, Algorithms, Data, Security, and Business stakeholders
Ensure production stability, CI/CD excellence, system reliability, and security
Lead capacity planning, hiring, onboarding, and performance management
Translate high-level strategy into execution plans and measurable outcomes
Foster a culture of ownership, accountability, and continuous improvement
Support architectural and design discussions when needed (hands-on leadership mindset)

We're building one of the most agentic, fast-moving AI products in the web search category - and we need a leader who can own it end to end. This is a cross-functional group leader role sitting at the intersection of AI product leadership and high-scale AI infrastructure: you'll lead the team building our agentic search product, and own the data infrastructure that indexes and caches the web at scale.
What Youll be Doing:
Set technical and product direction for an agentic web search AI system, from research and benchmarking through production and scale.
Bring deep, hands-on expertise in LLMs, agentic architectures, evaluation/benchmarking, and modern AI/LLMOps practices; make build-vs-buy and architecture calls with authority, not just strategy.
Lead and develop small group of two teams with top notch engineers, providing technical leadership, growing engineering managers, and driving execution across both product and infrastructure.
Drive the product to a category-winning position within an aggressive timeline.
Own the infrastructure supporting an API surface currently serving millions of calls/month, with a mandate to lead its growth to billions/month.
Bring proven, hands-on experience scaling high-throughput, high-availability infrastructure - not just AI-adjacent platform experience - including reliability, cost, and performance at that scale.
Own the data infrastructure needed to run the product, including large-scale data pipelines, storage, and operations.
Lead a worldwide web caching and indexing operation at high scale, ensuring freshness, coverage, and cost-efficiency of the index.