It starts with you - an AI Engineering Team Lead responsible for leading a team building production-grade agentic systems. This role combines hands-on technical leadership with people management, ownership of architecture, delivery, and quality across agents, MCP tools, agentic workflows, RAG systems, and evaluation.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Lead and mentor a team of AI Engineers building agentic systems and MCP tools.
Own technical direction for agent architectures, workflows, and LLM evals.
Review designs and code; ensure production readiness, reliability, and security.
Drive adoption of frameworks such as LangChain, LangGraph, or equivalent.
Set standards for RAG pipelines, vector databases, and retrieval quality.
Partner with product and platform teams on roadmap, scope, and delivery.
Balance hands-on contribution with people management and execution.
Build a culture of strong engineering practices, measurement, and iteration.

It starts with you - a senior AI engineer focused on building production-grade agentic systems: autonomous agents, MCP tools, agentic workflows, and rigorous evaluation.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Design and build single- and multi-agent systems with planning, memory, and tool use.
Implement and operate MCP tools and servers with secure schemas and permissions.
Build agentic workflows using LangChain, LangGraph, or equivalent frameworks.
Integrate LLMs via SDKs; manage prompts, structured outputs, and tool calling.
Define and run LLM evals (quality, correctness, latency, cost, regressions).
Add observability and reliability (logging, tracing, retries, state management).
Optimize performance and cost; take systems to production.
Mentor engineers and establish agentic best practices.

It starts with you - ML Engineering Team Lead responsible for leading a team delivering end-to-end ML systems. This role combines people management with ownership of model training, evaluation, deployment, and ML platform standards
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Lead and mentor ML Engineers delivering production ML systems.
Own technical direction for model architectures, training pipelines, and evals.
Review designs and code; ensure scalability, reliability, and data quality.
Define standards for experimentation, reproducibility, and monitoring.
Partner with product and platform teams on roadmap and prioritization.
Balance hands-on technical contribution with people management.
Build a culture of measurement, rigor, and continuous improvement.

We are seeking an experienced, hands-on Senior AI Engineer to join the Generative AI applications Platform group and lead the backend implementation and architecture of AI/LLM solutions - from agent graphs and tooling to RAG, streaming, and production deployment.
As a Senior ML Engineer you will
Design and own agent architectures - Build and evolve graph-based agent workflows (multi-node LLM flows, tool execution, routing, human-in-the-loop review gates) using LangGraph, with clear state schemas, checkpointing, and streaming to production.
Turn product and user needs into backend AI - Work with Engineers, Product, and Analysts to translate business problems into technical requirements and implementations, including agent types, tools, RAG pipelines, and configuration-driven behavior.
Design, develop, and deploy GenAI capabilities end-to-end - LangChain tools and integrations, RAG (retrievers, vector stores, agentic flows), structured outputs, and APIs for chat, Copilot-style integrations, and MCP.
Raise the bar on quality and reliability - Establish patterns for observability (e.g., LangSmith), error handling, content safety, bounded autonomy (tool schemas, review workflows), and evaluation systems so that AI behavior is predictable and auditable.
Mentor and align the team - Provide technical guidance on LLM backend architecture and LangGraph/LangChain best practices so the team can iterate quickly and safely.

Required Software Engineer - Al Platform
What this role is really about:
You're building our AI platform. The internal system that powers AI capabilities across Product, Customer Success, Sales, Operations, Data, and IT.
This is a full-stack role where you'll own features end-to-end: design React interfaces for AI workflows, build Lambda functions that orchestrate multi-agent processes, integrate with enterprise systems (Salesforce, Workato, Snowflake), and optimize costs and performance at scale. You'll work with cutting-edge AI while building production-grade systems that handle real business operations.
If you want to build something that directly enables business growth, work across the full stack with modern tech, and have ownership over a platform that the entire company depends on, this is your opportunity.
Job responsibilities:
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 process - 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 process -Develop evaluation harnesses, offline/online experiments, prompt-testing frameworks, and dashboards to balance quality, latency, and spend across all AI services.

We are seeking a Backend Team Lead to spearhead the development of ludeo.ai, our GenAI-powered product that enables users to generate interactive (gaming experiences) directly from prompts or video content. This is a high-impact leadership role at the intersection of backend architecture, multimodal AI, and real-time systems. You will architect and lead the AI engine that transforms unstructured inputs (text/video) into structured, interactive gaming playable moments.

What Youll Do

Lead & Mentor: Build and manage a high-performing backend/AI engineering team, drive architectural decisions, and foster rapid innovation while maintaining production-grade reliability.
Design AI-Native Systems: Architect scalable microservices powering complex AI workflows. Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding strategies, and vector database infrastructure (e.g., Pinecone, Weaviate, Milvus, PGVector). Optimize retrieval, prompt orchestration, latency, and cost.
Agentic Workflows: Design multi-agent systems using planner/executor/tool-calling patterns. Implement stateful, multi-step AI workflows with frameworks such as LangChain, CrewAI, AutoGen, or similar. Build evaluation, observability, and safety mechanisms for LLM systems.
Multimodal AI: Integrate multimodal models (vision + text) to understand video and translate it into structured form.
Scale & Infrastructure: Ensure robustness, security, and high availability on AWS/Kubernetes. Design distributed systems that handle real-time data and AI workloads efficiently.
Collaborate: Work closely with Product and Design to translate GenAI capabilities into stable, scalable production features.

Were looking for a Staff AI Engineer to join our growing AI and engineering group. This is a highly impactful role for someone who wants to shape how AI is embedded across products, platforms, and business operations-from early experimentation to production-scale systems.As a Staff AI Engineer, youll operate end-to-end: identifying opportunities, designing solutions, and delivering real business value using modern AI and LLM-based systems.

What you'll be doing
Design, build, and deploy AI-powered solutions across Supersonics products and internal platforms
Partner closely with product, data, engineering, and business stakeholders to identify and execute high-impact AI use cases
Architect and implement agentic workflows using frameworks such as LangChain, LangGraph, or equivalent
Integrate and operate LLMs via SDKs, including prompt design, structured outputs, tool/function calling, and guardrails
Lead technical decisions around AI evaluation, monitoring, observability, and quality measurement
Own AI initiatives from concept through production, including iteration, scaling, and long-term maintenance
Stay up to date with emerging AI technologies, models, and best practices, and help bring them into production thoughtfully

Required AI Backend Engineer
Tel Aviv-Yafo, Gush Dan, Israel
We offer the industrys only platform that fuses customer identity and anti-fraud solutions - customer identity management, identity verification, and fraud prevention.
We sell to industries with large, consumer-facing businesses such as: banking, financial services, insurance, fintech, gaming, ecommerce/retail, telco / media, utilities, etc.
About the Role:
As the AI Backend engineer, you will join a team of highly skilled machine learning engineers in developing and deploying advanced AI/ML solutions that power our identity and security products. Youll utilize technical skills to drive innovation, ensure delivery of high-impact projects, and scale our data-driven capabilities across the organization.
This role requires both strategic thinking and hands-on expertise. Youll be responsible for shaping the data science roadmap, mentoring a growing team, and collaborating with product, engineering, and business stakeholders to translate business challenges into practical machine learning solutions.
What youll do:
Design, develop, and maintain backend services for AI agents and tool integrations using latest technologies
Build scalable APIs and microservices that interface with LLMs and AI frameworks
Implement agent orchestration systems, tool calling mechanisms, and workflow engines
Optimize performance and reliability of AI-powered applications at scale
Develop data pipelines for training, evaluation, and monitoring of AI systems
Integrate with various LLM providers (OpenAI, Anthropic, etc.) and manage API interactions.

We are looking for a Technical Leader to lead the technical evolution of this group as we transition toward Native AI and Agentic architectures across both product and engineering. This role reports directly to the VP of Engineering and will play a critical role in shaping how AI-first and agent-driven systems are embedded into core event pipeline.
Youll combine deep technical leadership, hands-on architecture work, and strong cross-functional influence to guide the team through this transformation - while maintaining the performance, reliability, and scale our customers depend on.

What You Will Do
Lead the technical direction of the Event Management group, owning architecture and long-term evolution
Drive the transition of core event processing systems toward Native AI and Agentic solutions, including AI-driven enrichment, correlation, decision-making, and automation
Partner closely with Product, Data, and AI teams to translate product vision into scalable, production-ready systems
Design and review high-scale, high-throughput backend systems handling millions of daily events
Mentor and grow engineers, fostering a culture of technical excellence, ownership, and pragmatic innovation
Act as a technical thought partner to engineering leadership, contributing to org-wide architectural decisions
Balance innovation with operational rigor, ensuring reliability, performance, and security throughout the transition
Contribute to a culture of technical excellence, collaboration, and continuous improvement

Were on the lookout for a driven and experienced hands-on Engineering Team Leader to lead a group of engineers building the AI application foundation behind our next-generation cyber-AI product.
This team owns the core backend and frontend infrastructure that powers all user-facing applications - as well as the agentic and conversational frameworks that bring intelligence and automation into the experience.
As a hands-on leader, youll guide a talented team of engineers in designing and evolving the systems that enable every other Engineering group to create fast, scalable, and intelligent apps on top of our platform.
The Responsibilities
Lead a multidisciplinary team responsible for backend services, frontend frameworks, and AI agent infrastructure - the technical bedrock of our product experience.
Mentor engineers, grow the team, and foster a culture of technical excellence and innovation.
Design and build robust frameworks and systems that power all customer-facing applications.
Develop the agentic and conversational architecture enabling LLM-powered user interactions and intelligent workflows.
Collaborate with AI research, data, and product teams to seamlessly integrate AI-driven capabilities into production systems.
Define and drive the technical roadmap, ensuring scalability, developer productivity, and rapid iteration.