דרושים » AI » Founding AI Developer בחברת סטארט-אפ

We are looking for a visionary and deeply technical Chief Architect for Data, AI & GenAI Platforms to drive the architecture, tooling, and long-term technological direction of our enterprise data and GAI products and initiatives. This is a foundational leadership role that sits at the intersection of hands-on system design, cross-functional enablement, and long-term strategic innovation.
You will serve as the chief architect and technology strategist across all data, AI, and GenAI efforts-owning the blueprint that powers intelligent products, agent-based experiences, and scalable platforms. Your work will influence product design, platform infrastructure, governance models, and the broader technical ecosystem we operate in.
We are seeking someone with deep, hands-on experience building large-scale, production-grade data and AI systems-combined with the ability to mentor teams, influence engineering leaders, and partner with product and business leadership to deliver enterprise-scale transformation.
Key Responsibilities
Define and own the technology vision, architecture, and evolution roadmap for all data, ML/AI, and GenAI systems across the organization.
Lead the architectural design and hands-on guidance of scalable data pipelines, real-time analytics, AI agent platforms, model hosting infrastructure, and enterprise knowledge frameworks.
Oversee and connect multiple AI and data-related initiatives, including LLM agents, vector databases, RAG pipelines, MLOps, and enterprise data lakes-ensuring coherence, reusability, and security.
Establish and enforce technical standards, patterns, and tooling across teams to ensure high-quality engineering, model performance, and platform scalability.
Partner with product, engineering, and business leaders to align technology strategy with product goals, business outcomes, and customer needs.
Guide the evaluation and adoption of emerging technologies including open-source GenAI frameworks, fine-tuning platforms, orchestration tools, and scalable cloud-native architectures.
Mentor and support principal engineers, data scientists, platform leads, and architects-creating a culture of technical excellence, experimentation, and ownership.
Champion data quality, model explainability, AI governance, and responsible AI practices across the entire lifecycle.
Serve as a senior thought leader internally and externally-representing the company in technical forums, conferences, and customer engagements when needed.

Required Software Engineer - Al Platform
About Us
We help modern, mid-size businesses transform the way they manage people, giving HR and managers all they need to connect, engage, develop, and retain top talent. Since 2015, weve achieved consecutive triple-digit year-over-year growth, all backed by our amazing team of Bobbers from across the globe, making us the choice HRIS of over ~4500 midsize and multinational companies and over 1 Milion users.
Our HR platform is intuitive, data-driven, and built for the way people work today: globally, remotely, and collaboratively.
What this role is really about
Were building our internal AI Platform as a foundation that enables safe, scalable, and cost‑effective AI across the company. Our mission is to support internal business units in becoming more productive and driving business growth. As a Software Engineer on Business Innovation (Internal), youll develop high‑leverage platform capabilities used by Product, Customer Success, Sales, Operations, Data, and IT. Youll work across the entire stack, from APIs and services to data and UI. transforming business requi
Build core AI platform services - Design and implement agent orchestration, prompt management, RAG, Connectors, and evaluation pipelines that power AI experiences across the company.
Develop complex agentic workflows - Develop a multi-step workflow that coordinates tools and services with proper observability, guardrails, and cost controls (using OpenAI Agent SDK, LangGraph, or a similar framework).
Build LLM evaluation and optimization systems -Develop evaluation harnesses, offline/online experiments, prompt-testing frameworks, and dashboards to balance quality, latency, and spend across all AI services.
Ship the internal AI portal - Build user-facing products that democratize AI access: prompt directories, agent designers, templates, approval workflows, and more.
Ensure security and compliance - Develop RBAC, data classification, PII redaction, audit logging, and policy enforcement.
Create robust integrations - Connect the platform with Salesforce, NetSuite, Slack, Snowflake, HRIS, and other critical business systems.
Establish operational excellence - Implement CI/CD, testing strategies, monitoring/tracing, and SLOs for high-reliability services.
Enable developers - build SDKs, CLIs, and templates that help teams create safe, scalable AI workflows. Lead technical discussions and write design documentation.