דרושים » AI » Agentic Automation Engineer (Information Systems)

We are looking for an AI Builder to design, build, and maintain agentic AI-driven workflows that streamline and automate internal business processes across the company.
This role focuses on initiating and orchestrating AI agents, integrating them with existing systems, and reducing manual effort across Sales, Marketing, Order Management, Finance, HR, and more.
You will work closely with the Information Systems team and business stakeholders to turn repetitive, human-dependent processes into reliable, AI-powered flows.
This is a hands-on builder role, not a research or pure data science position.
Key Responsibilities:
Agentic AI & Automation:
Design and implement agent-based AI workflows to automate internal processes end-to-end
Build multi-step AI agents capable of:
Decision-making
Tool usage (APIs, SaaS tools, internal systems)
Escalation and exception handling
Continuously optimize AI flows to reduce human involvement while maintaining control and auditability
AI Tooling & Platforms:
Implement solutions using Agentic AI platforms, tools and frameworks, such as: OpenAI / Azure OpenAI / Copilot Studio / Gemini Enterprise, AWS bedrock (AgentCore), SFDC Agentforce
Low-code / no-code automation tools with AI capabilities (e.g., Make, Workato, UiPath, n8n)
Select and evaluate new AI tools to support internal automation initiatives
Systems Integration:
Integrate AI agents with internal systems such as: CRM (SFDC), ERP (NetSuite), ticketing systems (Jira)
Identity and access management
Monitoring, logging, and knowledge bases
Build and consume APIs to enable agent actions and data retrieval
Governance, Reliability & Security:
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.

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 We are seeking an experienced Senior Generative AI Engineer (LLMs & Agents) to join our AI squad at KPMG. This role blends deep hands-on engineering with architectural responsibility and client-facing advisory work.
You will design, build, and operate production-grade LLM and multi-agent systems, working on both greenfield initiatives and the evolution of existing GenAI platforms.
You will play a key role in shaping technical direction, best practices, and delivery standards across the GenAI practice.
Key Responsibilities:
GenAI Development & Implementation
Build end-to-end GenAI solutions from POC through production deployment
Design and implement backend microservices architectures for GenAI applications using Pytho
Design, implement, and maintain production-grade Python services with a focus on code quality, performance, and reliability
Architect and develop multi-agent systems, orchestration layers, and autonomous workflows
Integrate and optimize LLMs and GenAI APIs across complex systems
Evaluate and improve system performance, scalability, reliability, and cost efficiency
Client Engagement & Advisory
Lead technical discussions with clients and translate business needs into technical architectures
Present GenAI solutions, design decisions, and trade-offs to technical and non-technical stakeholders
Provide strategic technical guidance on GenAI adoption and system design
Cloud & Platform Ownership
Deploy and manage GenAI systems across GCP, Azure, and AWS
Leverage cloud-native AI services (Vertex AI, Azure OpenAI, SageMaker, etc.)
Own production environments, monitoring, and operational excellence
Continuous Learning & Practice Development
Evaluate emerging GenAI models, frameworks, and techniques
Define and refine best practices for GenAI system development and deployment
Contribute to internal accelerators, methodologies, and knowledge sharing

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.

The Falcon Cloud Security team is looking for a hands-on Engineering Manager / Team Lead to lead the development of Agentic Workflows - a transformative initiative aimed at automating complex security operations using AI-native agents. You will lead a team of talented engineers while remaining deeply technical, helping architect and build autonomous systems that don't just alert but actively reason, investigate, and remediate security risks across multi-cloud environments.
As a player-coach, you will help shape the "brain" of our cloud security platform, guiding both the people and the technology that leverages large-scale data and AI-driven logic to help customers discover misconfigurations, prioritize risks, and automate defensive actions at scale.

What You'll Do:

Lead & Grow a Team: Manage, mentor, and develop a team of backend engineers, fostering a high-trust, high-performance culture. Conduct regular 1:1s, support career growth, and drive hiring to scale the team.

Stay Hands-On: Remain an active technical contributor - designing, reviewing, and writing production-quality code alongside your team. Lead by example and maintain a strong engineering presence.

Design & Architect: Drive backend engineering efforts to build autonomous agentic frameworks, guiding the team from rapid prototypes to large-scale production applications.

Develop Core Logic: Contribute to and oversee the development of decision-making engines and workflows that allow security agents to interact with cloud APIs (AWS, Azure, GCP) and internal data streams.

Data Integration: Guide the development of high-performance data integrations and streaming services (Kafka) to feed real-time security data into agentic models for continuous reasoning.

Scale Systems: Architect and oversee distributed systems capable of processing billions of security events to provide actionable posture intelligence and automated remediation.

Drive Cross-Functional Collaboration: Partner with Product, Design, and peer engineering teams in a "startup-like" environment to define and deliver new platform capabilities with speed and quality.

Raise the Bar: Champion engineering excellence, new technologies, and best practices across the team and broader engineering organization.

We're looking for a Senior AI/MLOps Engineer to join a group that specializes in Security and Networking, and specifically ML, AI and agent development. As a Senior AI/MLOps Engineer, youll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, security architects and DevOps teams to ensure smooth deployment, modeling and optimization of AI models. This role involves creative problem solving alongside engineering teams, and is pivotal for the continued success of AI networking security.

What youll be doing:

Developing, improving and optimizing scalable infrastructure for handling and deploying security and networking AI models and agents in production, ensuring high availability, scalability, reproducibility, and performance.

Optimizing AI models and agents for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

Monitoring and deploying agentic systems, LLMs, and ML models in production.

Designing and implementing frameworks/pipelines for AI training, inference, and experimentation.

Collaborating closely with data scientists, security architects and software engineers to operationalize and deploy AI models and agents, including packaging and integration with existing systems. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.

Collaborating with DevOps teams to integrate pipelines and workflows into the CI/CD process, ensuring flawless deployments and rollbacks.

Building and maintaining monitoring and alerting systems to proactively identify and resolve issues relating to quality, performance and infrastructure.

Implementing access controls, authentication mechanisms, and encryption standards for AI models and data.

Documenting guidelines, and standard operating procedures for MLOps/AI processes and sharing knowledge with the wider team.

Develop proof-of-concepts for new features.

The AI Business Solutions team within Technology Consulting AI department is looking for a Low Code / No Code Implementer to join our innovative and fast-growing team.
Our team designs and delivers advanced solutions across multiple platforms to build systems, applications, websites, chatbots, and especially AI Agents for clients across diverse industries in Israel and globally. The role involves hands-on work building and implementing solutions using modern platforms and tools, combining technical execution with business understanding in a project-based client environment.
Key Responsibilities:
Build and implement AI and automation solutions across various platforms
Design and configure systems, workflows, and intelligent agents
Work closely with clients to analyze business requirements and translate them into working solutions
Integrate multiple tools and technologies into end-to-end solutions
Participate in innovative AI projects

The Falcon Cloud Security team is looking for a hands-on Engineering Manager / Team Lead to lead the development of Agentic Workflows - a transformative initiative aimed at automating complex security operations using AI-native agents. You will lead a team of talented engineers while remaining deeply technical, helping architect and build autonomous systems that don't just alert but actively reason, investigate, and remediate security risks across multi-cloud environments.
As a player-coach, you will help shape the "brain" of our cloud security platform, guiding both the people and the technology that leverages large-scale data and AI-driven logic to help customers discover misconfigurations, prioritize risks, and automate defensive actions at scale.

What You'll Do:

Lead & Grow a Team: Manage, mentor, and develop a team of backend engineers, fostering a high-trust, high-performance culture. Conduct regular 1:1s, support career growth, and drive hiring to scale the team.

Stay Hands-On: Remain an active technical contributor - designing, reviewing, and writing production-quality code alongside your team. Lead by example and maintain a strong engineering presence.

Design & Architect: Drive backend engineering efforts to build autonomous agentic frameworks, guiding the team from rapid prototypes to large-scale production applications.

Develop Core Logic: Contribute to and oversee the development of decision-making engines and workflows that allow security agents to interact with cloud APIs (AWS, Azure, GCP) and internal data streams.

Data Integration: Guide the development of high-performance data integrations and streaming services (Kafka) to feed real-time security data into agentic models for continuous reasoning.

Scale Systems: Architect and oversee distributed systems capable of processing billions of security events to provide actionable posture intelligence and automated remediation.

Drive Cross-Functional Collaboration: Partner with Product, Design, and peer engineering teams in a "startup-like" environment to define and deliver new platform capabilities with speed and quality.

Raise the Bar: Champion engineering excellence, new technologies, and best practices across the team and broader engineering organization.

As an RPA Developer, you will develop and maintain software solutions that automate business processes and lead initiatives related to the design and management of workflow automation projects.
Responsibilities:
Design, develop, and test automation workflows with various systems
Deploy RPA components, including bots, robots, developmental tools, code repositories, and logging tools.
Collaborate with cross-functional teams to define and deliver projects that meet business needs.
Work with stakeholders to capture business requirements and translate them into technical designs and strategies.
Troubleshoot production issues.
Support the launch and implementation of RPA solutions.
Create, maintain, and support existing robots.
Design and develop user interfaces for RPA interaction.
Develop and maintain RPA framework libraries.
Produce test documentation and carry out testing of automated solutions.
Create process and end-user documentation.
Assist with quality assurance of the automation.
Drive the adoption of best practices around coding, design, quality, and performance.

We are always looking for exceptional talent to join us on the journey!
Your Mission:
As an MLOps Engineer, your mission is to design, build, and operate the platforms that power our machine learning and generative AI products spanning real-time use cases such as large-scale fraud scoring, MCP & agentic workflows support. Youll create reliable CI/CD for models and Agents, robust data/feature pipelines, secure model serving, and comprehensive observability. You will also support our agentic AI ecosystem and Model Context Protocol (MCP) services so that models can safely use tools, data, and actions across.
You will partner closely with Data Scientists, Data/Platform Engineers, Product, and SRE to ensure every model from classic ML to LLM/RAG agents moves from prototype to production with strong reliability, governance, cost efficiency, and measurable business impact.
Responsibilities:
Operate & Develop ML/LLM platforms on Kubernetes + cloud (Azure; AWS/GCP ok) with Docker, Terraform, and other relevant tools
Manage object storage, GPUs, and autoscaling for training & low-latency model serving
Manage cloud environment, networking, service mesh, secrets, and policies to meet PCI-DSS and data-residency requirements
Build end-to-end CI/CD for models/agents/MCP tooling (versioning, tests, approvals)
Deliver real-time fraud/risk scoring & agent signals under strict latency SLOs.
Maintain MCP servers/clients: tool/resource definitions, versioning, quotas, isolation, access controls
Integrate agents with microservices, event streams, and rule engines; provide SLAs, tracing, and on-call runbooks
Measure operational metrics of ML/LLM (latency, throughput, cost, tokens, tool success, safety events)
Enforce governance: RBAC/ABAC, row-level security, encryption, PII/secrets management, audit trails.
Partner with DS on packaging (wheels/conda/containers), feature contracts, and reproducible experiments.
lead incident response and post-mortems.
Drive FinOps: right-sizing, GPU utilization, batching/caching, budget alerts.