לוח משרות דרושים AI Engineer, לחיפוש זה נמצאו 150 משרות

We're hiring a Technical Enablement Specialist to own the rollout and adoption of AI and engineering, product and design enablement across our Product-Technology org. This is a sole-function, high-impact role - you will be the person who takes approved strategy and turns it into real execution, visible adoption, and measurable outcomes. This role reports directly to the Director of Product-Engineering Operations.
If you are a get-it-done person who loves working with people, knows how to drive change without heavy process, and is excited about where AI is taking software development - this role was written for you.
About the Role:
Lead AI adoption across Product-Technology - own the rollout of AI tools, agents, and AI-first practices; identify blockers and drive follow-up actions to move toward higher AI-generated code
Drive Agentic SDLC adoption - translate approved solutions and guidelines from Leadership into practical, consistent rollouts, including the POC framework and experimentation guidelines
Build scalable enablement programs - use AI to design and produce learning assets, workshops, and self-serve resources that keep pace with a fast-moving engineering org
Own knowledge management - maintain Confluence as the single source of truth for AI and engineering enablement; close content gaps with documentation, playbooks, and best practices
Foster a culture of continuous learning - coordinate the Engineering Forum, Engineering Guild, Product Guild, and AI community channels; identify opportunities for growth and keep the org current on AI tooling and industry trends
Partner with leadership and measure impact - collaborate with Product-Technology leadership to anticipate needs, define success metrics, and continuously improve programs based on data and feedback

We're looking for an experienced Senior Software Engineer with experience in building AI based products to join our Insights Business Unit. You'll play a crucial role in building AI-powered features that turn our digital shelf and market share data into actionable insights, working alongside a talented and passionate team.
Responsibilities:
End-to-end feature development for AI-powered analytics on rich datasets, from architecture to production.
Mentor teammates and partner with Product, Data Science, and Design to deliver reliable conversational flows.
Design secure, low-latency data retrieval and AI integration pipelines (function calling, agentic workflows, etc) for internal datasets and APIs.
Build and scale integrations to data sources - defining schemas, queries, and caching strategies; continuously improve backend components to deliver a top‑notch user experience with efficient resource trade‑offs.
Establish quality guardrails, automated tests/evaluations, and observability; optimize for scalability, performance, and cost; run A/B tests.
Optimize context engineering and data retrieval strategies - balancing relevance, latency, and token efficiency to deliver accurate AI-powered insights.

we are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.

You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.
What you'll be doing:

Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.

we are looking for a Senior Software Engineer to join the AI Engineering team in a role focused on embedding directly with business teams to drive AI transformation. Be at the forefront of Applied AI. This role is outward-facing: you will engage with GTM and G&A functions - Sales, Marketing, Finance, HR, Legal, Customer Success - and fundamentally alter how these teams operate with AI.
What you will be doing:

Embed with GTM and G&A teams (Sales, Marketing, Finance, HR, Legal, Procurement, Customer Success) to identify, scope, and prioritize the highest-impact AI opportunities within each function, and act as both product manager and engineer for these initiatives.
Own the full lifecycle of each solution, from requirements gathering through deployment to adoption measurement and iteration, with a focus on business outcomes.
Serve as the primary technical partner and AI advisor for business function leaders, translating their needs into engineering plans and helping them develop their own AI fluency.
Develop and deliver hands-on AI enablement and training for non-R&D teams, building their ability to use AI tools independently and effectively.
Collaborate with the team to leverage shared infrastructure (MCP servers, RAG systems, evaluation frameworks, guardrails) while feeding back requirements from the field.
Measure and report on AI adoption impact - unlocking new opportunities, process improvements, and capability gains - to build the case for continued investment and to guide prioritization.

We are looking for a Staff AI Platform Engineer to join the Development Platform team, which is responsible for accelerating our R&D velocity and elevating product quality.
We need a pragmatic systems thinker who is deeply passionate about Developer Tools (DevTools) and the future of generative AI. You can architect a distributed LLM workflow in the morning, and influence engineering behavior across the entire org in the afternoon.
In this role, you will enable 200+ engineers to safely and reliably leverage agentic AI.
What You'll Do:
Scale Quality, Not Just Code Volume: Solve the hard problem of AI-driven quality by building rigorous measurement frameworks, ensuring that an AI-accelerated org delivers better software, not just more software.
Establish AI Governance & Security: Architect guardrails around LLM usage, data privacy, and cost management, ensuring 200+ engineers can innovate rapidly without compromising compliance or security.
Optimize the SDLC: Embed autonomous workflows, coding agents, and tool/context design directly into the developer lifecycle to supercharge R&D velocity.
Drive Org-Wide Adoption: Act as a force multiplier, leading the organizational rollout of AI developer tooling and setting production best practices across teams.
Build Agentic Infrastructure: Design and deploy production-grade multi-agent systems, tackling complex challenges like parallel session isolation, subagent delegation, and self-improving feedback loops.

We are seeking talented, motivated AI builders to join our Strategic Initiatives team as part of a new AI Center of Excellence. Reporting to the Sr. Director of Engineering, this team designs and ships AI-native solutions - agents, assistants, and reusable skills - that advance our security mission and multiply the impact of teams across the company.
This is a builder role. We're looking for experts engineers fluent in modern AI application development - agent frameworks, harnesses, tool use, prompting, retrieval, and evaluation - not machine learning engineers. You will be expected to train foundation models / frontier models . You will compose capable, production-grade AI systems on top of frontier models, get them into people's hands, and bring the rigor to prove they actually work.
What you'll do:
Design, build, and bring to production ready: models, AI agents, assistants, and reusable skills that solve real problems for us and our customers.
Turn ideas into working MVPs fast, then partner with engineering to harden them into reliable, production-ready systems.
Build evaluation into everything you ship - define what "good" means for each solution, measure it, and hold the bar. Due diligence through rigorous evals is non-negotiable, not an afterthought.
Compose agentic workflows that are secure by construction, using secure harnesses along with appropriate isolation, guardrails, and controls.
Select and integrate the right frameworks, tools, and models for each job, and turn what works into reusable patterns and best practices for the COE.
Also be a part of the COE Consult team to help across the organization.
Document what you build and how it should be used, operated, and evaluated.

We're hiring the engineering leader who will own its AI core.
Small senior team, greenfield architecture and real production environments from day one. You'll be one of the founding technical leaders - writing code, shaping the architecture, and growing the team as the product scales.
What You'll Do:
Agent Architecture & Engineering:
Design and build the AI systems at the center of the product: researcher agents, deterministic runners, multi-agent orchestration across thousands of targets and hundreds of sites.
Own the full agent stack - LLM selection and behavior, RAG pipelines, tool use, memory, evaluation, and observability. Make architectural decisions that will define how the product works for years.
Drive adoption of the modern agent ecosystem: LangGraph, MCP, semantic tool discovery, hybrid edge/cloud workflows, A2A patterns. Keep pushing the frontier.
Safety & Reliability:
Design for progressive autonomy: pre-checks, fault tolerance, rollback, and full audit trails. In our customers' environments - critical infrastructure, enterprise security - a wrong action has real consequences.
Build the evaluation and observability pipelines that make autonomous agent behavior trustworthy and debuggable in production.
Partner with Security and DevOps on agent execution boundaries, especially across on-prem ↔ cloud data flows.
Technical Leadership:
Spend most of your time in the codebase. Set the technical bar by example - architecture, code quality, and engineering judgment.
Establish standards for testing, evaluation, and safe deployment of AI systems. Build the practices that scale with the team.
Work directly with the PM and enterprise design partners to shape the roadmap. Your decisions will drive the product, not just execute it.
Team:
Start with a small senior group, grow it deliberately. Hire well, mentor, and shape the engineering culture of a startup inside a public company.

We're looking for exceptional backend engineers who understand modern AI systems and enjoy building the infrastructure and products around them.
Our team is creating the foundational technologies that allow AI agents to operate safely, securely, and reliably at scale. This includes building secure agent control planes, embedded controls, developer tooling, observability, and infrastructure that enables production-ready AI systems.
This is a hands-on engineering role for someone who enjoys building products from the ground up. You'll partner closely with AI researchers and backend engineers to rapidly move ideas into production.
What You'll Do:
Design and build secure AI infrastructure for production AI agents.
Develop Agent Control Plane capabilities that manage, monitor, and secure agent execution.
Build embedded controls and security mechanisms directly into AI agents.
Develop reusable services, APIs, and developer tooling that support AI applications.
Build and maintain integrations with modern Agent SDKs and Model Context Protocol (MCP).
Design backend microservices using Python and AWS.
Build observability into AI systems, including telemetry, monitoring, tracing, and operational visibility.
Develop public-facing developer tools and command-line interfaces (CLI).
Partner closely with AI researchers to rapidly transition prototypes into production-ready systems.
Own projects from architecture through deployment.
Help define engineering standards and reusable patterns across the AI platform.
Collaborate with senior engineers while independently leading technical initiatives when appropriate.

As a developer on the Big Data Platform, you will be a part of the outstanding group that builds intelligent data infrastructure, directly powering context-aware AI models and autonomous workflow automation. We are looking for people who look at engineering differently-people who are passionate about scaling AI-ready data layers, optimizing real-time context streaming, and leading the smart platform solutions they envision. If you are passionate about developing a cutting-edge data foundation that drives conversational AI execution across enterprise applications, making a massive impact, and striving to work with the industrys best talent!

What will you actually be doing?
End to end development of features and systems that are used daily by key stakeholders, both internally and externally

A technical focal point for software development best practices and design of main components, services and systems.

Explore, implement, and introduce cutting-edge technologies and innovative ideas.

We are looking for people who are passionate about leading technology to the extreme. If you are striving to develop an innovative product, make an impact, and work with the industrys brightest talent as part of one of the fastest-growing and successful startups around


What will you actually be doing?
End to end development of features and systems that are used daily by key stakeholders, both internally and externally.

A technical focal point for software development best practices and design of main components, services and systems.

Integrate AI into the company applications.

Improve development workflow with AI capabilities.

Be part of an organic team developing in a fast paced environment based on CI/CD.

Investigate, implement and share new technologies and ideas.

DRS RADA is a leading defense high-tech company specializing in radar systems development. We are seeking a talented AI Engineer to join our AI group and take part in the research and development of new AI-based capabilities and products. In this role, you will work on a wide range of AI challenges, from early-stage exploration and development to supporting the integration of solutions into operational systems. This role includes working with different radar data modalities and offers an opportunity to contribute to meaningful, cutting-edge technologies in a multidisciplinary environment. Key Responsibilities: · Research, develop, and evaluate AI models and algorithms for new product capabilities. · Explore new ideas and transform them into practical AI-based solutions. · Analyze complex time-series data and extract insights to support model development and product decisions. · Work closely with AI and software engineers within the team and take responsibility to bring new solutions into operational systems. · Develop clean, efficient, and maintainable Python code for model development and experimentation. · Stay updated with industry trends, research methods, and emerging technologies in AI and data science.

We're a team of Data Scientists, each owning a different model and domain of expertise. We're looking for a Senior AI Engineer to join us - someone who thinks fast, learns independently, and gets from problem to working solution quickly. You'll own your own models end-to-end while also raising the bar for how the whole team builds, evaluates, and ships ML.



What You'll Do

Design, build, and improve ML/AI models across domains - recommendation systems, image recognition, chatbots, and beyond.
Own the full ML lifecycle: data preprocessing, feature engineering, training, validation, and deployment to production.
Build evaluation pipelines that prove performance, scalability, and consistency - and that the rest of the team can reuse.
Apply generative AI and LLMs to improve existing workflows and identify new product opportunities.
Partner with Product, Engineering, and Analytics to keep modeling work tied to real business outcomes.
Translate complex model behavior and findings into insights stakeholders can act on.
Bring technical judgment to the team - share what you learn, and help keep practices consistent across different models and domains.