דרושים » הנדסה » AI Developer

We are looking for a Hands-On Agentic AI Engineer to join a new team focused on applying AI agents and intelligent workflows to improve business processes across the organization.
The ideal candidate is someone who enjoys building real-world AI-driven solutions end-to-end - writing code, designing architectures, building prototypes, solving implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI solutions.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
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 and IS teams 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.

We are looking for a Hands-On Agentic AI Engineer to join a new team focused on applying AI agents and intelligent workflows to improve business processes across the organization.
The ideal candidate is someone who enjoys building real-world AI-driven solutions end-to-end - writing code, designing architectures, building prototypes, solving implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI solutions.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
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 and IS teams 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.

We are looking for a Hands-On Team Lead - Agentic Engineering to lead, build, and actively contribute to a new team focused on applying AI agents, and intelligent workflows to improve business processes across the organization.
This role is both a technical leadership role and a hands-on engineering role. The successful candidate will manage the first Agentic Engineer, help grow the team, and personally contribute to the design, development, integration, and deployment of agentic AI solutions.
The ideal candidate is someone who can lead from the front: writing code, designing architectures, building prototypes, reviewing technical work, solving complex implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI-driven solutions.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
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 and IS teams 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.

Were looking for a hands-on Agentic AI Engineer to build practical, high-impact AI solutions that transform how our teams operate.
This is not a research role. Youll design and ship real AI systems that improve workflows across Sales, Marketing, HR, and Operations - building custom solutions where off-the-shelf tools fall short.
If you enjoy turning messy business problems into production-ready AI systems using LLMs,SLMs, agents, and smart data pipelines - this role is for you.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots) using frameworks like LangGraph / LangChain
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
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.

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 AI 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 an Senior AI Engineer to design, build, and deploy AI-powered capabilities within our product.

This role focuses on integrating machine learning models and large language models (LLMs) into scalable software systems and delivering reliable AI-driven features to production.

The AI Engineer works at the intersection of software engineering, AI systems, and infrastructure. transforming AI technologies into practical applications.

Responsibilities:
Build applications powered by machine learning and large language models (LLMs).
Implement capabilities such as intelligent assistants, semantic search, automation, and recommendation systems.
Integrate AI functionality into backend services and product workflows.
Design and implement retrieval pipelines, embedding pipelines, and inference workflows.
Build Retrieval-Augmented Generation (RAG) systems and AI-driven services.
Create scalable AI architectures capable of handling production workloads.
Package and deploy AI models as production services.
Optimize inference performance, scalability, and latency.
Monitor AI services to ensure reliability and performance.
Develop backend services and APIs that expose AI capabilities.
Integrate AI systems with databases, internal services, and external APIs.
Contribute to system architecture and microservices design.
Implement logging, metrics, and observability for AI systems.
Track model performance and system reliability in production environments.
Work closely with product managers, engineers, and data scientists.

abra professional services is seeking for an AI Engineer (GenAI & Integration) The AI Engineer (GenAI & Integration) designs, builds, and deploys AI-powered solutions within enterprise systems and business workflows. The role focuses on practical application of AI by integrating models, data, and tools into real operational environments to enable automation, decision support, and productivity gains. The role emphasizes implementation and integration rather than model development, bridging AI capabilities with enterprise systems and workflows. Key Responsibilities
* Design and implement end-to-end AI solutions aligned with business needs
* Integrate AI capabilities with enterprise systems, APIs, and data platforms, including legacy environments
* Develop AI agents and automation workflows for multi-step task execution
* Build AI-driven applications, including copilots and decision-support tools
* Develop and maintain integration layers, including MCP-based and similar AI integration services
* Evaluate, test, and validate AI outputs to ensure accuracy, reliability, and quality in production
* Deploy, monitor, and optimize AI solutions in production environments
* Maintain clear and structured documentation across solutions, integrations, and processes
* Lead implementation of AI solutions in collaboration with business, IT, and engineering teams to ensure scalable and compliant delivery

Were expanding our Data & AI group and looking for a passionate, experienced Senior Data & AI Engineerto join our mission. This is a unique opportunity to work at the intersection of data engineering, LLMpowered systems, agentic workflows, and cybersecurity innovation

What youll work on
Data Infrastructure & EngineeringDesign, build, and scale production-grade data pipelines using Databricks, Spark, and modern cloud-nativetechnologies. Ensure high standards of data integrity, system performance, reliability, and scalability.
Core Backend & PlatformDesign and contribute to scalable backend services and platform capabilities using microservices andevent-driven architectures. Build reliable APIs, integrations, and asynchronous data flows that support highscale AI, data, and cybersecurity use cases.
LLM & Agentic SystemsDesign, prototype, and integrate LLM-powered systems, including Retrieval-Augmented Generationpipelines, agentic workflows, tool-using agents, multi-step reasoning flows, and AI-driven automation. Workwith technologies such as AWS Bedrock, OpenAI, Anthropic, LangGraph, vector databases, and modernorchestration frameworks.
AI-Assisted Engineering & Developer ProductivityExplore and apply advanced AI coding assistants and software-engineering agents, such as Codex andClaude Code, to improve development velocity, code quality, debugging, testing, and experimentation.Build proof-of-concepts and internal tools that help engineering and research teams work more effectivelywith AI-powered development workflows.
Intelligent Cybersecurity FeaturesCollaborate with Security Researchers, Engineers, and Product teams to identify opportunities forintelligent, data-driven features that deliver actionable cybersecurity insights to customers. Transformcomplex cybersecurity and platform data into reliable, explainable, and useful AI-powered capabilities.

We are looking for a hands-on, business-minded AI Engineer to join our Data & AI Team.
This role is for someone who has already built and shipped real AI products in a company environment. You will work as an integral part of the Data & AI Team, partnering directly with business stakeholders to identify high-impact opportunities, translate business needs into technical solutions, and build AI products that automate internal processes and create immediate value.
The ideal candidate is a builder. You should be comfortable working with LLMs, AI agents, automation workflows, APIs, data pipelines, data warehouses, and internal company systems. You should also be comfortable taking ownership, asking sharp business questions, and moving ideas from concept to production.
Our Data Team has already built internal AI products at our company. Now we are looking for someone who can help take us to the next level.
What Were Looking For
The right person has built with AI in a real company environment and knows how to turn business needs into practical internal products. They should be comfortable working with stakeholders, understanding how teams operate, and identifying where AI can create meaningful value.
Because this role sits inside the Data & AI Team, they also need to be strong with data. That means working confidently with company data, data warehouses, pipelines, APIs, and the technical building blocks that make AI products reliable and useful.
This role is for someone hands-on, curious, and hungry to build. Someone who can combine AI, data, and business context to help us move faster, automate smarter, and turn ideas into measurable business wins.
What Youll Do
Build end-to-end internal AI products, automations, agents, and workflows that solve real business problems across our company.
Work directly with business stakeholders to understand pain points, define requirements, and turn ideas into scalable AI-driven solutions.
Design, prototype, test, deploy, and maintain production AI products using LLMs, AI agents, APIs, automation frameworks, and internal company data.
Work hands-on with data tools and infrastructure, including Snowflake, ETLs, data pipelines, APIs, AI tools, and internal servers.
Identify high-impact manual processes and turn them into automated AI-driven business wins.
Evaluate new AI tools, frameworks, and agentic workflows, and apply them where they can improve productivity, decision-making, or business operations.
Help shape internal AI development best practices around reliability, usability, security, documentation, maintainability, and production readiness.

We're hiring a software engineer to work directly with our business teams - finance, sales, legal - building tools and automations that help them do their jobs better. You'll write production code and own what you build, but most of your time will be spent understanding business processes and how to impact them.
Most business teams have more day-to-day operational pain than they realize, and a lot more they could be doing with AI than they know. Your job is to find those gaps and build something that fixes them. Success looks like the team being able to move faster and spend their time on the work that matters, because everything else just runs.
You'll have a lot of autonomy in this role. You'll decide what to work on, build it, ship it, and see whether it actually made a difference. You'll be doing this as part of a small, senior AI team, so while the day-to-day work is independent, you'll have other engineers to collaborate with and a shared bar for how we build things.
What You'll Be Doing:
Build & Engineer:
Take the lead on technical implementation and be the owner of how it all works - picking the right tool for the job (code, no-code, or otherwise) and keeping the knowledge of the system in your handsDesign and deliver end-to-end AI solutions - from first stakeholder conversation through production deployment and iteration
Implement LLM-powered systems: RAG pipelines, AI agents, multi-step automations, and tool-integrated workflows
Integrate solutions with enterprise systems (Salesforce, NetSuite, Slack, Data platforms) and build for production: observable, reliable, and cost-optimized
Embed With the Business:
Work directly with Finance, Sales, HR, Legal, and Customer Success to identify and scope high-leverage AI opportunities
Translate ambiguous business needs into concrete engineering plans; own both the solution definition and the build
Help business stakeholders develop AI fluency and become stronger partners over time