דרושים » תוכנה » Generative AI Engineer

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 an Associate Generative AI Engineer to join our AI squad . This role blends hands-on engineering with exposure to system design and client-facing delivery, making it an excellent opportunity for engineers early in their career to work on real, production-grade GenAI systems.
You will design, build, and operate LLM-based and agentic systems as part of cross-functional teams, contributing to both greenfield initiatives and the evolution of existing GenAI platforms. You will develop strong foundations in system architecture, backend engineering, and cloud-based GenAI delivery while working closely with more experienced engineers.
Key Responsibilities:
GenAI Development & Implementation:
Develop end-to-end GenAI solutions from POC through production deployment
Implement backend microservices and GenAI components using Python
Contribute to the development of multi-agent systems, orchestration layers, and autonomous workflows
Integrate and optimize LLMs and GenAI APIs within larger system
Participate in evaluating and improving system performance, scalability, reliability, and cost efficiency
Client Engagement & Collaboration:
Participate in technical discussions with clients and contribute to solution design discussions
Support presentations, demos, and technical explanations for client stakeholders
Collaborate closely with project managers, full-stack developers, and automation teams to deliver end-to-end solutions
Cloud & Platform Work:
Deploy and operate GenAI systems on GCP, Azure, and/or AWS
Work with cloud-native AI services and managed platform
Contribute to monitoring, reliability, and operational stability of production environments

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.

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.

we are seeking a Hands-on Architect to design, build, and evolve the core of next-generation AI cybersecurity platform.This is not an ivory-tower role; it is for a builder at heart.
You will write code, build functional prototypes, and own critical services from inception to production.
This role demands a unique blend of deep, code-level execution with a broad, system-wide architectural vision that spans our entire data, cloud, and AI stack.
Responsibilities:
Rapidly code and build functional proofs of concept (PoCs) and prototypes to explore and validate new architectures, data platforms, data processing frameworks, and GenAI capabilities.
Validate technical feasibility, scalability, and business impact through working software, not just diagrams or documents.
Partner closely with engineering, product and data science teams to translate emerging technologies into production-ready, scalable systems.
Lead architecture design reviews, proactively identify scalability and performance bottlenecks, and embed security principles into the design process from day one.
Serve as a technical leader and mentor, elevating the team's skills through pair programming, in-depth code reviews, and deep-dive sessions on system design and software craftsmanship.

Cloud is now one of the biggest business expenses-and one of the hardest to manage.
At our company, were not just shedding light on spend-were giving companies the power to make smarter, faster, and more strategic decisions about the cloud.
Were trusted by brands like The New York Times, Wiz, Elastic, SiriusXM, and Lyft, and backed by top-tier investors with over $85M raised. In just 4 years, weve grown to 100+ people across Tel Aviv and New York-and were just getting started.
If youre looking to build something big, solve real problems, and grow fast-wed love to meet you.
Were looking for a Generative AI Developer to join our forward-thinking engineering team. This role is perfect for someone with a passion for cutting-edge AI, a strong software engineering background, and the creative spark to identify and implement novel use cases within our product.
You will play a critical role in adding AI capabilities to our FinOps SaaS platform. Whether it's enhancing user workflows, automating insights, or inventing entirely new product experiences, youll have both the freedom and support to experiment and execute.
our company provides a uniquely rich dataset covering the full scope of a companys cloud spend. This expansive data playground offers a powerful foundation for experimentation and insight generation, enabling the development of intelligent, value-driven features.
Responsibilities:
Lead the charge in transforming our product and preparing it for the agentic age.
Design, build, and deploy generative AI-powered features across our product.
Identify opportunities for AI integration by proactively exploring FinOps use cases and user needs
Prototype and validate new AI use cases quickly and iterate based on internal and external feedback
Collaborate cross-functionally with product, design, and backend teams to drive innovation from concept to production
Stay current with the fast-moving generative AI landscape and evaluate new models, APIs, and tools (e.g., OpenAI, Anthropic, Hugging Face, AWS Bedrock, open-source LLMs).
Live in the future and track new innovations and paradigms in this fast evolving field and identify opportunities to integrate them into the product
Implement safeguards, prompt engineering techniques, and usage monitoring to ensure high-quality AI outputs
Optimize model performance, inference time, and cost efficiency within AWS infrastructure.

Were looking for an Sr Solutions Architect responsible for advising on Generative AI, core services and also to provide technical pre-sales guidance to strategic customers while building long-term relationships, identifying pain points, and addressing them.
📍 Work location - hybrid from Tel-Aviv
Responsibilities:
Strategic Advisory: Act as a technical and strategic advisor in the field to provide architectural guidance in the GenAI space and recommendations necessary to promote & help customers overcome technical challenges and scale securely on AWS.
Pre-Sales Architecture: Serve as a pre-sales Solutions Architect to guide customers on best practices and ensure cost optimization.
Relationship Management: Build strong connections with internal and external stakeholders, from technical teams to senior executives.
Business Growth: Collaborate with Account Executives to drive service adoption and ensure success in the long term.
Travels: locally (on-demand to meet with customers and partners and attend local events) and abroad (at least once a quarter).

we are where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner and Strategic Partner, we deliver hands-on DevOps and FinOps and GenAI support that drives real results.
We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.
Were looking for an Sr Solutions Architect responsible for advising on Generative AI, core services and also to provide technical pre-sales guidance to our company strategic customers while building long-term relationships, identifying pain points, and addressing them.
Work location - hybrid from Tel-Aviv
Key Responsibilities
Strategic Advisory: Act as a technical and strategic advisor in the field to provide architectural guidance in the GenAI space and recommendations necessary to promote & help customers overcome technical challenges and scale securely on AWS.
Pre-Sales Architecture: Serve as a pre-sales Solutions Architect to guide customers on best practices and ensure cost optimization.
Relationship Management: Build strong connections with internal and external stakeholders, from technical teams to senior executives.
Business Growth: Collaborate with Account Executives to drive service adoption and ensure success in the long term.
Travels: locally (on-demand to meet with customers and partners and attend local events) and abroad (at least once a quarter).

This is a role for someone who wants to shape the fundamentals of our platform, both technically and strategically. Youll lead the design of scalable GenAI systems and connectivity to other platforms and tools, define effective AI best practices, mentor engineers, and influence how AI is built across the company all while staying deeply hands-on.

Its about ownership and impact: building, leading, and shaping impact end-to-end.
What You'll Do:
Lead the architecture and implementation of scalable GenAI solutions.
Define and enforce AI best practices: evaluation, privacy, responsible AI, and performance.
Drive AI strategy across teams and products.
Read, interpret, and apply cutting-edge AI research.
Design infrastructure that enables AI at scale-from zero-to-one to production.
Mentor engineers and grow technical leadership across the organization.

we are looking for a Senior AI Engineer.
Responsibilities:
Identify high-impact opportunities to leverage AI and AI agents to automate and optimize internal workflows.
Design, architect, and implement end-to-end AI-driven solutions - from problem definition to production deployment and adoption.
Integrate AI systems with internal platforms, services, APIs, and third-party tools.
Collaborate with technical and non-technical stakeholders to translate business needs into practical, scalable solutions.
Take full ownership of solutions, including iteration, performance optimization, monitoring, and long-term maintenance.
Evaluate and adopt new AI tools, frameworks, and methodologies with a pragmatic, business-oriented approach.