member of technical staff, product (ai agents)

sales executive (m/w/d) für agentic workplace transformation

director, it engineering - end user support

(junior) cloud site reliability engineer (network) (m/f/x)

(senior) engineer, software ivv test & integration, iris2

(senior) fullstack engineer (typescript) - client success platform (m/f/x)

member of technical staff, product (ai agents) Jobs in Munich

applied ai engineer

full stack ai engineer

research engineer (agentic models) Jobs in Munich

research engineer (agentic models)

sales executive (m/w/d) für agentic workplace transformation Jobs in Munich

research engineer agentic models

JetBrains

<div>
 At JetBrains, code is our passion. Ever since we started, back in 2000, we&rsquo;ve been striving to make the strongest, most effective developer tools on earth. Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs.
 
 
 We&rsquo;re building multi-step coding agents that can understand large codebases, plan changes, call tools, and iterate with the user. As a Research Engineer in the Agentic Models team, you&rsquo;ll be responsible for the models, training loops, and evaluation pipelines that power these agents.
 
 
 You&rsquo;ll work at the intersection of SFT and RL-style post-training, and product-driven evaluation, using our distributed GPU and MapReduce clusters to ship models into JetBrains products.
 
 
 
 As Part Of Our Team, You Will
 
 
 
 <ul>
 <li>
 Design, implement, and maintain SFT and RL post-training pipelines for multi-step coding agents.
 </li>
 <li>
 Train and adapt LLMs for agent workflows, including planning, tool use, and multi-step interactions inside JetBrains IDEs.
 </li>
 <li>
 Build and develop evaluation and simulation environments where coding agents can act, be measured, and compared on realistic developer tasks.
 </li>
 <li>
 Design evaluation frameworks and metrics for agent behavior, analyze traces and logs, and close the loop from evaluation back into training, data, and reward design.
 </li>
 <li>
 Analyze training and evaluation results to propose and implement improvements to model architectures, training recipes, and datasets.
 </li>
 <li>
 Work with large-scale infrastructure, including distributed training on GPU clusters and large MapReduce-style data processing for pre-training and fine-tuning datasets.
 </li>
 <li>
 Collaborate closely with research, product, and infrastructure teams to turn high-level product visions into concrete models, experiments, and shipped features.
 
 
 </li>
 </ul>
 We&rsquo;ll be happy to bring you on board if you have:
 
 
 <ul>
 <li>
 Extensive hands-on experience training LLMs (pre-training, fine-tuning, or post-training) in a research or production setting.
 </li>
 <li>
 Deep expertise in modern deep learning frameworks such as PyTorch, and specialized LLM training stacks (e.g. Megatron, NeMo, verl, or similar).
 </li>
 <li>
 Strong theoretical and practical understanding of LLM fundamentals: architectures, tokenization, data pipelines, batching, mixed precision, distributed training, and debugging unstable runs.
 </li>
 <li>
 The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
 </li>
 <li>
 A product-aware mindset &ndash; you care about how developers actually use agents and can translate product needs and failure modes into modeling and evaluation work.
 </li>
 <li>
 At least 3 years of Python experience writing clean, maintainable code in modern ML codebases.
 
 
 </li>
 </ul>
 
 Our Ideal Candidate Would Have Experience With
 
 
 
 <ul>
 <li>
 ML orchestrators and workflow tools such as Kubeflow, Dagster, Airflow, ZenML, and/or job schedulers like Kubernetes or SLURM.
 </li>
 <li>
 Large-scale data and training pipelines, e.g. MapReduce-style clusters, multi-node GPU training, or workloads on the order of 1M+ CPU/GPU hours.
 </li>
 <li>
 Designing and maintaining evaluation pipelines for LLMs or agents, including metrics, dashboards, experiment tracking, and automated regression checks.
 </li>
 <li>
 AI agent development, such as tool-using agents, planners, or multi-step coding workflows, and familiarity with agentic frameworks or patterns.
 </li>
 <li>
 Experiment tracking and observability using tools like Weights &amp; Biases, MLflow, Langfuse, or similar.
 </li>
 <li>
 Inference optimization and serving optimized models in production.
 
 
 </li>
 </ul>
 
 We are an equal opportunity employer
 
 
 
 We know great ideas can come from anyone, anywhere. That&rsquo;s why we do our best to create an open and inclusive workplace &ndash; one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
 
 
 
 We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
 
 
 
</div>

Research Engineer (Agentic Models)

NVIDIA

<div>We are looking for a Senior Software Engineer, Applied AI Systems, to build production AI / ML and agentic solutions. We need a hands-on senior engineer who can turn ambiguous technical problems into durable software systems and AI-enabled systems: agents, workflow services, APIs, data pipelines, tool integrations, evaluation and benchmarking harnesses, reference architectures, and operational tooling.
We work at the intersection of applied AI, agentic workflows, software engineering, distributed systems, performance engineering, accelerated computing, and data infrastructure. In this role, you will build AI systems as real software systems: write and review high-quality code, make architecture tradeoffs, benchmark behavior and performance, and outcomes from prototype through validation, hardening, deployment, and ongoing support. This is an opportunity to shape how production applied AI systems are built, measured, and reused inside NVIDIA!
We partner across global teams and time zones for design reviews, planning, debugging, support critical issues, and technical decision-making. We need an engineer who turns complex requirements into clear technical plans, keeps the focus on reusable software capability rather than one-off delivery, and drives execution across teams.
What you will be doing:
<ul><li>Build and own production-grade applied AI systems for NVIDIA&rsquo;s technical and solution development use cases, including agentic solutions where they materially improve the systems and softwares.</li><li>
Design and build agentic workflows and the software around them: workflow services, APIs, retrieval, MCP/A2A-style tool integrations, agent harnesses, automation, telemetry, operational controls, and human oversight.</li><li>
Design reliable services, APIs, workflow state, event-driven execution, and observability using systems such as Kafka, ClickHouse, and OTel-style patterns.</li><li>
Translate complex technical and operational requirements into clear system designs, plans, interfaces, measurable outcomes, and pragmatic technical decisions through design reviews, code reviews, and clear communication.</li><li>
Develop production software in Python and other relevant languages, with strong testing, observability, CI/CD, documentation, and operational practices.</li><li>
Build performance and benchmarking workflows for existing production solutions or products, including validation harnesses, regression tests, tracing, metrics, failure analysis, latency, throughput, reliability, resource usage, and AI/inference behavior where relevant.</li><li>
Improve standard solution patterns alongside larger applied AI systems, working with NVIDIA engineering and solution teams to codify repeated patterns, product gaps, and field lessons into APIs, services, reference architectures, playbooks, test harnesses, and shared engineering building blocks.</li><li>
Debug and support production solutions across software, infrastructure, AI models, data pipelines, inference services, and GPU-accelerated environments, turning recurring support patterns into product or platform improvements.</li></ul>
What we need to see:<ul><li>
BS, MS, or PhD in Computer Science, Engineering, AI/ML, or equivalent experience, with 5+ years of professional software engineering experience owning production systems or meaningful platform components.</li><li>
Hands-on experience with LLM, generative AI, RAG, agentic AI, MCP or intelligent AI technologies beyond simple prompting or notebooks, including tool use, retrieval, evaluation, guardrails, orchestration, or human-in-the-loop control.</li><li>
Strong Python engineering skills and practical experience with at least one additional production programming language such as C++, Go, Rust, or TypeScript.</li><li>
Demonstrated ability to develop and build distributed systems, backend services, data pipelines, workflow orchestration, APIs, or developer platforms using production environments like Kafka, ClickHouse, PostgreSQL, Redis, object storage, Kubernetes, or similar technologies.</li><li>
Strong system design and operational judgment, including reliability, latency, cost, security, privacy, scalability, debuggability, maintainability, performance analysis, benchmarking, profiling, or capacity evaluation.</li><li>
Excellent debugging and problem-solving skills across software, infrastructure, AI systems, and performance bottlenecks.</li><li>
Proven ownership of ambiguous, cross-team engineering work, with ability to collaborate with distributed teams spanning US Pacific, EMEA, and APAC timezones.</li><li>
Required : Strong written and verbal communication skills in English.</li></ul>
Ways to stand out from the crowd:
<ul><li>Experience building real-world AI implementations, agent tools, MCP-compatible modules, A2A-style bridges, agent frameworks, evaluation frameworks, or RAG systems used by real users.</li><li>
Familiarity with NVIDIA GPU, AI Software Technologies such as NVIDIA NIM, NeMo Agent Toolkit, CUDA and Agentic AI development frameworks</li><li>
Open-source contributions, technical papers, patents, conference talks, engineering blogs, or major internal engineering artifacts</li></ul>
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Widely considered to be one of the technology world&rsquo;s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/</div>

Senior Software Engineer, Applied AI

CLERA

<div><h3 class="jobSectionHeader">About the Role</h3>
This is a founding-level product role at a seed-stage B2B SaaS company building AI-powered tools that help sales teams work smarter &mdash; automating note-taking, CRM updates, meeting preparation, and conversation intelligence, all in a GDPR-compliant, privacy-first way. The product spans Web, Desktop, and Mobile.
As the Founding Product Manager, you'll partner directly with the CTPO and leadership team to shape product vision and build a scalable, high-quality product organization from the ground up. This is a high-ownership, high-impact role that blends strategic thinking with hands-on execution.<h3 class="jobSectionHeader">
What You'll Do</h3><ul><li>
Shape Product Vision &amp; Strategy: Co-own the product roadmap and long-term vision alongside the CTPO, ensuring alignment across engineering, design, and executive stakeholders.</li><li>
Own Product Discovery &amp; Delivery: Drive the full product lifecycle end-to-end &mdash; from user research and ideation through delivery, launch, and iteration.</li><li>
Build AI-First &amp; Agentic Experiences: Lead the design and delivery of AI-powered and agentic product features that create real, measurable value for users.</li><li>
Drive Cross-Platform Coherence: Ensure a consistent, high-quality product experience across Web, Desktop, and Mobile surfaces.</li><li>
Build Product Processes &amp; Level Up the Org: Establish best-in-class product processes, define success metrics and KPIs, and help grow the product function as the company scales.</li></ul><h3 class="jobSectionHeader">
What We're Looking For</h3>
Required:<ul><li>
3+ years of experience as a Product Manager, with a focus on technically complex, engineering-heavy products</li><li>
Proven track record delivering AI-powered features or products, including managing the AI product lifecycle</li><li>
Experience as a Founding or Lead PM, with demonstrated ability to align cross-functional teams (engineering, design, executives)</li><li>
End-to-end ownership of products from discovery through delivery and iteration</li><li>
Strong data-driven decision-making with well-defined success metrics and KPIs</li><li>
Strong technical fundamentals &mdash; either through a technical education background or hands-on engineering experience</li><li>
Fluency in German is required</li></ul>
Nice to Have:<ul><li>
Background as a software engineer or in a technical role prior to transitioning to product management</li><li>
Experience in B2B SaaS, sales tech, or conversation intelligence</li><li>
Familiarity with CRM ecosystems and integrations</li></ul><h3 class="jobSectionHeader">
Location</h3><ul><li>
On-site in Munich, Germany</li><li>
Visa sponsorship is available</li></ul></div>

Founding Product Manager

Integrity Next

<div><h4 class="jobSectionHeader">Join us!</h4>
At IntegrityNext, we are building a shared AI and data platform on AWS on top of our supply chain and product compliance platform. This platform will power semantic data access, BI, APIs, and agentic product experiences across our product landscape. 
As AI Application Engineer (m/f/d), you will build and ship AI-powered product capabilities end-to-end. You will work hands-on across Python-based AI services, agent workflows, web and document retrieval pipelines, unstructured data processing, APIs, integrations, and lightweight React prototypes where needed. 
Our AI application layer is built around LangChain, LangGraph, Deep Agents, and Amazon Bedrock AgentCore. The focus is on product delivery rather than research, covering both structured-data-driven AI experiences and unstructured-data processing for retrieval, agent workflows, and future AI-native product capabilities. 
We work according to &ldquo;You build it, you run it&rdquo;, own capabilities from design to production operations, follow spec-driven development, and actively use AI-assisted engineering tools such as Claude Code, Cursor, and similar tools.<h4 class="jobSectionHeader"> 
What can you expect?</h4>
Build agentic AI product capabilities<ul><li>
Build AI-powered product features using retrieval mechanisms, workflows, tools, and multi-step agent patterns</li><li>
Turn product and business needs into reusable, reliable AI capabilities for internal and customer-facing use cases</li><li>
Implement AI capabilities in Python using LangChain, LangGraph, Deep Agents, and Bedrock AgentCore</li><li>
Design and build AI APIs with clean service boundaries for integration into Java-based product systems</li></ul>
Work with structured, unstructured, web, and document data<ul><li>
Build and maintain retrieval and unstructured-data processing pipelines for documents, web content, and other sources used in agent workflows</li><li>
Work with content and PDF extraction, link following, candidate ranking and selection, deduplication, and source or provenance tracking</li><li>
Collaborate with platform and semantic teams to ground AI features in reliable, well-structured data</li><li>
Support AI experiences based on structured business data, semantic layers, and analytics-driven use cases</li></ul>
Improve AI quality, reliability, and production readiness<ul><li>
Drive prompt engineering and context engineering to improve quality, reliability, and usability</li><li>
Implement evals, regression checks, prompt-injection tests, scenario-based validation, and quality controls</li><li>
Help define evaluation harnesses, testing approaches, and validation methods for agentic and retrieval systems</li><li>
Support AI observability, tracing, quality monitoring, maintainability, and production operations</li></ul>
Contribute across product and engineering layers<ul><li>
Contribute to lightweight frontend prototypes and conversational or workflow-driven UI flows in React where needed</li><li>
Work closely with semantic, data platform, architecture, product, and engineering teams</li><li>
Help establish practical spec-driven and AI-assisted engineering workflows that improve quality, speed, and maintainability</li></ul><h4 class="jobSectionHeader">
What should you bring along?</h4>
Experience &amp; Domain Focus<ul><li>
Strong practical experience with Python and proven experience building AI-powered product features in production or near-production environments</li><li>
Experience with LLM application development, including agentic RAG, tool use, workflow orchestration, prompt engineering, and context design</li><li>
Strong knowledge of agentic AI concepts such as agent workflows, planning patterns, tool usage, multi-step reasoning architectures, and agent harnesses</li><li>
Experience building multi-step agents or pipelines that retrieve, read, and reason over information from web and document sources with a focus on grounding, attribution, and reliability</li><li>
Experience building or maintaining unstructured-data pipelines for AI applications, including document and web-page processing, text extraction, retrieval, and AI-oriented data preparation</li><li>
Experience designing backend APIs and integrating AI capabilities into larger product landscapes through clear service boundaries</li></ul>
Technical / Methodological Skills<ul><li>
Hands-on experience with LangChain and/or LangGraph</li><li>
Familiarity with Deep Agents or similar multi-step or planning-oriented agent harnesses is a strong plus</li><li>
Knowledge of Amazon Bedrock AgentCore and strong overall AWS knowledge, including OpenSearch, S3, and DynamoDB</li><li>
Experience with web search APIs such as SERP API, Linkup, or Tavily, and crawling or extraction frameworks such as Firecrawl or Crawl4AI</li><li>
Experience with headless or JS-rendering fetching using tools such as Playwright or Puppeteer</li><li>
Comfortable with content and PDF extraction, link following, candidate ranking and selection, deduplication, and source or provenance tracking across varied, multilingual, and often unreliable web sources</li><li>
Experience with MCPs, A2A, AgentCore Gateway, Agent Skills, Agent plugins, and testing these components</li><li>
Experience with evaluation harnesses, regression testing, prompt-injection testing, and quality controls for AI and retrieval systems</li><li>
Experience with observability, tracing, or monitoring for AI or backend systems</li><li>
Ability to contribute to lightweight frontend or prototype work in React when needed</li></ul>
Ways of Working &amp; Mindset<ul><li>
Strong product delivery mindset with a focus on building and shipping AI-powered capabilities end-to-end</li><li>
Comfortable owning AI-powered features in production, not just prototyping them</li><li>
Strong quality mindset and the ability to improve AI systems through testing, evaluation, iteration, and harness-based validation</li><li>
Comfortable working with structured specifications, clear interfaces, spec-driven development, and AI-assisted engineering workflows</li><li>
Deep specialization in AI engineering combined with the willingness to contribute across adjacent layers when needed</li><li>
Practical, hands-on approach to solving complex product and platform challenges</li></ul>
Communication &amp; Collaboration<ul><li>
Comfortable collaborating closely with semantic, data platform, architecture, product, and engineering teams</li><li>
Able to work across backend implementation, AI application development, APIs, and lightweight frontend prototyping</li><li>
Strong ability to translate product and business needs into reliable technical capabilities</li><li>
Clear communication style and willingness to share knowledge across teams</li><li>
Fluent English skills for working effectively in an English-speaking environment</li></ul>
Nice to have<ul><li>
Experience with large-scale or polite crawling, deduplication, and source or provenance tracking</li><li>
Experience with entity resolution and attribution across heterogeneous web sources</li><li>
Experience with multilingual document and web-content processing and retrieval</li><li>
Experience designing agentic architectures, evaluation harnesses, and quality frameworks for AI systems</li><li>
Experience with AI observability and tracing tools</li><li>
Experience with React and frontend prototyping for conversational or workflow-driven experiences</li><li>
Experience working with structured business data, semantic layers, or analytics-driven AI use cases</li><li>
Experience with advanced document pipelines, retrieval systems, and unstructured-data-based AI features</li><li>
Experience in multi-team SaaS environments</li></ul><h4 class="jobSectionHeader">
What do we offer?</h4><h3 class="jobSectionHeader">
Purpose &amp; Impact</h3><ul><li><div>
A role with real meaning that is both enjoyable and impactful</div></li><li><div>
The opportunity to make a sustainable contribution through your work</div></li><li><div>
Attractive compensation as part of a growing company</div></li></ul><h3 class="jobSectionHeader">
Attractive Benefits</h3><ul><li><div>
30 days of paid vacation</div></li><li><div>
EGYM Wellpass membership to support your work-life balance</div></li><li><div>
Flexible working models to better balance work and personal life</div></li></ul><h3 class="jobSectionHeader">
Modern Work Environment &amp; Flexibility</h3><ul><li><div>
Inspiring office spaces in the heart of Munich</div></li><li><div>
Flexible remote work from home or anywhere within Germany</div></li></ul><h3 class="jobSectionHeader">
Great Team</h3><ul><li><div>
A professional, welcoming, and highly motivated team</div></li><li><div>
Collaboration at eye level with an open feedback culture</div></li><li><div>
An environment where people support each other and grow together</div></li></ul><h3 class="jobSectionHeader">
Flat Hierarchies &amp; Ownership</h3><ul><li><div>
Short decision-making paths and real opportunities to shape things</div></li><li><div>
Freedom to contribute and implement your own ideas</div></li><li><div>
A high level of ownership and responsibility</div></li></ul><h4 class="jobSectionHeader"> 
Application process</h4>
Please apply exclusively via our online application portal. This ensures a smooth and fair process for all candidates. Applications submitted by email or LinkedIn will not be considered. Thank you for your understanding.<h4 class="jobSectionHeader">
About us</h4>
IntegrityNext, a global leader in supply chain sustainability software, stands at the forefront of corporate sustainability and compliance. Since 2016, businesses have trusted IntegrityNext to simplify ESG compliance, reduce risks, and address critical challenges like due diligence, decarbonization, and sustainability reporting. With over 500 customers and 2 million suppliers across 190 countries, IntegrityNext is transforming supply chains into engines of transparency and sustainable growth. For more information, visit www.integritynext.com. 
 
We are an equal opportunity employer and do not discriminate based on race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We welcome applicants from all backgrounds and strive to create an environment where everyone feels respected and heard. Join us in our mission to build a more equitable and inclusive world.</div>

Full Stack AI Engineer (m/f/d)

Salesforce

<div>To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Sales
Job Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn&rsquo;t a buzzword &mdash; it&rsquo;s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
<h2 class="jobSectionHeader">About the Role
</h2>Technical depth required. Architectural judgment expected.
Salesforce is hiring Senior Forward Deployed Engineers &mdash; the Technical Builders, responsible for deciding that leads who design, build, and deploy the most complex agentic AI solutions directly inside enterprise customer environments. You'll lead technical delivery on your team, mentor the next wave of engineers, and set the engineering standards that define how agentic AI gets deployed at scale. Partnering closely with a Deployment Strategist ( Strategic Builder - a customer-facing advisor who shapes AI strategy and drives adoption), you'll own outcomes end-to-end, from architecture decision to production. Your passion for well-crafted software that solves real problems will be supported by best-in-class AI tools and a team of talented builders around you.
The Senior Builder Experience
<ul><li>Technical Ownership: Partner with a Deployment Strategist to own customer outcomes end-to-end. You're the senior technical authority in the room, ensuring deliverables meet the highest engineering standards, whether it was generated by an AI tool by a colleague or written by you directly.
</li><li>AI-Supported Engineering: Cursor, Claude, and Salesforce coding products like Vibes are embedded in your daily workflow. The conventions and patterns you develop tend to propagate through the team because other Builders look to your work as reference.
</li><li>Roadmap Influence: Your field experience routes directly to Product and Engineering. The gaps you hit and the edge cases you encounter in real life customer environments become the features they ship. Senior Forward Deployed Engineers are the most credible voice in agentic AIproduct evolution.
</li><li>Continuous Innovation: You're expected to stay at the forefront &mdash; piloting emerging AI tools, experimenting with new models and frameworks, and sharing what you learn with your team and customers.
</li></ul>What You'll Actually Be Building
<ul><li>Own end-to-end build and deployment of agentic AI solutions for Salesforce's most strategic customers &mdash; from architecture decisions through production handoff.
</li><li>Design and ship agentic systems on the Agentforce platform: agent logic, tool calls, multi-agent orchestration, deterministic guardrails, and the integration patterns that hold up in enterprise environments. Your reference implementations become the basis for how other Builders approach similar problems.
</li><li>Own the data lifecycle: model design, processing pipelines, and data readiness for AI applications across Salesforce Data 360, Snowflake, Databricks, and customer-specific platforms.
</li><li>Resolve the technical blockers that other engineers can't &mdash; data integration failures, model deployment issues, orchestration breakdowns, performance regressions. These problems are routed to you because of your track record of solving them.
</li><li>Build and maintain agent performance dashboards and customer KPI reporting to track deployment health and business outcomes across engagements.
</li><li>Develop proofs-of-concept and MVPs quickly, with the judgment to know which decisions can be deferred and which need to be right the first time.
</li><li>Codify what you learn. The patterns, reusable assets, and internal frameworks that come out of your real customer work become the playbooks the rest of the org draws from.
</li><li>Mentor other Engineers through code reviews, pair sessions, and shared work. Most of your influence on developing engineers happens inside the same codebases you're building in.
</li><li>Provide technical depth on at-risk or strategically critical deployments when senior engineering judgment is needed.
</li><li>Surface field insights directly to Product and Engineering. The gaps and edge cases you encounter in real customer environments are some of the most valuable inputs to the Agentforce roadmap.
</li><li>Partner with the Deployment Strategist on your team to translate complex customer business challenges into agentic solutions that actually ship.
</li></ul>You're Our Senior Forward Deployed Engineer If&hellip;
<ul><li>Your fluent in German and English
</li><li>You have 6+ years of software engineering or technical delivery experience, with proven end-to-end ownership of scalable production systems in enterprise AI, cloud, or SaaS environments.
</li><li>You have a degree in Computer Science or a related field
</li><li>You're an expert in at least one of Python, JavaScript/TypeScript, Java, or Apex, and conversant in the others.
</li><li>You've integrated LLMs into production, used frameworks like LangChain or LlamaIndex, and applied prompt engineering and responsible AI practices in real customer contexts.
</li><li>You have deep experience in data modeling, processing, and analytics, with demonstrable proficiency across platforms like Salesforce Data 360, Snowflake, or Databricks.
</li><li>You bring deep Salesforce platform expertise: Agentforce, Apex, LWC, Flows, and Salesforce APIs.
</li><li>You have an entrepreneurial, get-things-done mindset focused on fast, impactful delivery &mdash; and the judgment to know when &quot;fast&quot; is the wrong call.
</li><li>You've mentored technical talent and created reusable assets &mdash; frameworks, playbooks, internal tooling.
</li><li>You communicate clearly and credibly with engineering peers, customer architects, and executive stakeholders.
</li><li>You actively tinker with the evolving AI/data landscape &mdash; piloting new tools, experimenting with new models, and staying genuinely curious about what's coming next.
</li><li>You're excited to travel ~25% of the time, embedded with customer engineers.
</li></ul>Nice-to-Haves
<ul><li>Salesforce certifications (Administrator, Platform Developer I/II, Agentforce Specialist, System Architect)
</li><li>Familiarity with DevOps/CI-CD practices, observability tooling, or data governance frameworks
</li><li>Experience architecting multi-cloud, multi-system enterprise AI solutions for Global 500 customers
</li><li>Track record of influencing enterprise software product roadmaps through field engineering insight
</li><li>Open-source contributions, published technical writing, or conference presentations
</li></ul>Unleash Your Potential
When you join Salesforce, you&rsquo;ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we&rsquo;ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future &mdash; but to redefine what&rsquo;s possible &mdash; for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates&rsquo; resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
We warmly invite applications from individuals with a severe disability status (Schwerbehinderung). Salesforce is committed to equality and creating a workplace that reflects society. We set ambitious goals for representation, emphasize accessibility and inclusion, and continuously learn and improve. Learn more about our inclusion initiatives here (https://www.salesforce.com/company/accessibility/workplace-resources/#ally-sf-benefits). In 2019, Salesforce joined The Valuable 500 to champion disability inclusion in business leadership.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that&rsquo;s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications &ndash; without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.</div>

Senior Forward Deployed Engineer (Technical Builder)

Siemens

<div><div>Transform the everyday</div><div><div><div><div>
Siemens builds the systems the physical world runs on: factories, power grids, buildings, trains, hospitals. Industrial and physical AI is a major opportunity in applied AI, and one of the harder ones to get right. There is a generation of AI-powered products to build.
We are an applied science organization building the science behind them. The work sits at the intersection of machine learning research, real world data, and production systems running in industrial environments.
As Principal Applied Scientist, you lead the science on a major capability area inside the pod. You take ambiguous problems through hypothesis, method selection, experimentation, and into models that run in production. You are hands on with the modeling, and you are accountable for the rigor and the outcome.
This is a senior individual contributor role. You will work in close partnership with engineers and product managers who turn your work into product.<div>
As part of our team, you will have</div></div></div><ul><li>
An attractive remuneration package</li><li>
Appealing Siemens pension benefits</li><li>
Access to employee share plans</li><li>
30 days of paid vacation and a variety of flexible work schedules that allow time off for you and your family</li><li>
2 to 3 days of mobile working per week as a global standard</li><li>
Up tp 30 days workation per year in certain countries</li></ul>
Since each of over 300,000 team members feels that other benefits are particularly important, and we cannot list our entire benefit portfolio here, you can find more information here. 
 
The individual benefits are subject to regulatory, contractual, or corporate conditions.
You&rsquo;ll make an impact by<ul><li>
Own one or more scientific capability areas end to end, for example perception, computer vision, language and agents, time series, control, planning, or evaluation</li><li>
Take problems from ambiguous product or system requirements through clear research questions, hypotheses, and success metrics</li><li>
Lead applied research projects: literature review, method selection, experimentation, ablation, error analysis, and productization</li><li>
Build and run the evaluation pipelines for the work you own: offline metrics, online experiments, robustness testing in industrial conditions</li><li>
Work with engineers to take models into production grade pipelines: data readiness, training infrastructure, inference, observability</li><li>
Make scientific tradeoffs in front of engineers and product managers, with evidence, and translate them into decisions the team can act on</li><li>
Identify and de-risk scaling challenges in your area: data quality, model drift, latency, throughput, cost, safety</li><li>
Raise the bar on experimentation rigor, reproducibility, and documentation across the team</li><li>
Apply responsible AI practices in your work: bias detection, model risk management, human in the loop controls</li></ul></div></div><div><div>
This how you'll win us over<ul><li>
Education</li><li><ul><li>
Master&acute;s degree or an equivalent qualification in Computer Science, Machine Learning, or a related field</li></ul></li><li>
Experience &amp; Skills</li><li><ul><li>
8+ years in applied machine learning, AI research, or data science, with models that shipped to production and made an impact</li><li>
Strong foundation in machine learning theory and practice across training, evaluation, and deployment</li><li>
Demonstrated experience taking research from a paper or prototype into a model that runs reliably in production</li><li>
Proficiency in Python and modern ML frameworks and toolchains</li><li>
Strong partnership track record with engineering teams on data, training infrastructure, and inference</li><li>
Clear written and verbal communication with engineers, product managers, and senior leaders</li></ul></li><li>
Preferred Qualifications:</li><li><ul><li>
Experience applying ML in industrial or physical domains: manufacturing, automation, robotics, energy, mobility, infrastructure, healthcare</li><li>
Deep expertise in one of: multimodal ML, generative AI, retrieval augmented generation, agentic workflows, time series, control, or planning</li><li>
Scientific ML for physical systems: surrogate modeling, operator learning, physics-informed ML, geometry-aware ML, differentiable simulation, AI for semiconductor/EDA</li><li>
Hands-on experience building evaluation pipelines, running online experiments, or instrumenting production monitoring for a model you owned</li><li>
Publications, patents, open source contributions, or significant internal technology transfers</li><li>
Experience mentoring more junior scientists and engineers</li><li>
Experience working with globally distributed research, product, or engineering organizations</li></ul></li><li>
Ways of working: You operate with high autonomy, lead scientific excellence, and collaborate closely across engineering and product teams</li><li>
Languages: business proficiency in English</li></ul><div>
You are much more than your qualifications, and we believe in the potential of every single candidate. We look forward to getting to know you!</div></div></div><div><div> 
Your individual personality and perspective are important to us. We create a working environment that reflects the diversity of the society and support you in your personal and professional development. Let&rsquo;s get to know your authentic personality and create a better future together with us. As an equal-opportunity employer we are happy to consider applications from individuals with disabilities.
About us
To transform the everyday, you need to think outside the box. That&rsquo;s why we at Siemens are looking for innovators who aren&rsquo;t afraid to push boundaries to join our diverse team of tech experts. Got what it takes? Then help us create lasting, positive change!
www.siemens.de/careers &ndash; if you would like to find out more about jobs &amp; careers at Siemens.
FAQ &ndash; if you need further information on the application process.</div></div></div><div></div>

Principal Applied Scientist (f/m/d)

techtree

About the RoleA leading frontier AI company is looking for an Applied AI Engineer to join their Solutions team in Munich.This is a customer-facing technical role, but the balance is heavily technical: roughly 20% involves presales support, onboarding, and client guidance - the other 80% is designing, developing, and deploying AI solutions for B2B enterprise clients.Your stakeholders are technical. You won't be simplifying things for non-technical audiences - you'll be working directly with data scientists, software engineers, and CTOs on complex, high-impact implementations.This is not a consultancy role. You'll operate with the mindset of a startup CTO embedded in a world-class AI team: owning projects end-to-end, shipping working solutions, and collaborating closely with researchers and product engineers on the company's most challenging customer problems.What You'll Do<ul><li>Deploy AI solutions into production across various industries, delivering measurable business impact</li><li>Build state-of-the-art GenAI applications - from consumer products to industrial use cases</li><li>Develop complex implementations involving fine-tuning, advanced RAG pipelines, agentic workflows, and custom LLM applications</li><li>Participate in presales calls to understand client needs and provide technical guidance</li><li>Collaborate with researchers and product engineers on the team's most demanding customer projects</li><li>Feed customer insights back into product and model development</li></ul>How the Team Works<ul><li>What matters is what you ship, not the time you spend on it</li><li>No bureaucracy - you talk to whoever you need to, the best idea wins</li><li>Low ego, high standards; direct, honest feedback</li><li>Unstructured environment where people find joy in ambiguity</li></ul>About You<ul><li>Fluent in English and German (required for this Munich-based role)</li><li>2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products</li><li>Proven experience implementing AI/ML products with APIs, back-end and front-end interfaces</li><li>Hands-on experience with fine-tuning LLMs, advanced RAG, or agentic use cases</li><li>Deep understanding of machine learning concepts and the algorithms underlying LLMs</li><li>Strong Python coding skills</li><li>Able to explain complex technical concepts clearly to technical audiences</li></ul>Nice to Have<ul><li>Open-source contributions, especially in the LLM space</li><li>Prior experience as a Customer Engineer, Forward Deployed Engineer, Solutions Architect, or Technical PM</li><li>Experience with PyTorch and deep learning</li></ul>Compensation<ul><li>Base salary + equity</li></ul>Job Type: Full-timePay: 61.504,42&euro; per yearApplication Question(s):<ul><li>Cover letter</li><li>Expected Salary</li></ul>Work Location: In person

Applied AI Engineer

Explore 100+ Research engineer agentic models in Munich this July. Find roles across top companies and apply now to boost your career.