Senior AI Engineer (f/m/d)

What To Expect
Tesla is revolutionizing the automotive industry with sustainable energy and advanced manufacturing. As a Data Engineer in the Paint Shop, you will help harness production data to optimize paint processes, support quality assurance, and improve operational efficiency. Working alongside senior engineers, you will build and maintain the data pipelines that integrate real-time data from paint lines, inspection systems, and automation tools, and turn it into datasets and dashboards the team relies on. Collaborating with cross-functional teams (Production Engineering, Controls, and Quality), you will help enable data-driven decisions that support Tesla's mission of accelerating the world's transition to sustainable energy through high-volume, defect-free vehicle production. This role suits an engineer with a solid technical foundation who wants to grow their impact in a fast-paced manufacturing environment.

What You'll Do

• Data Pipeline Development: Build, maintain, and optimize ETL (Extract, Transform, Load) pipelines that process data from Paint Shop systems, including sensor data from coating robots, inspection cameras, and cycle time trackers. Contribute to pipeline design and keep them robust and integrated with Tesla's data platforms (e.g., cloud systems like AWS, Azure, or internal tools).

• Data Integration and Management: Integrate data sources from manufacturing equipment (e.g., automated lines, EHS sensors, ERP systems) into unified datasets for analysis. Help maintain data lakes, warehouses, and streaming pipelines that support monitoring of paint quality, defect rates, and throughput. Deliver dashboard requests (e.g., for production metrics or defect tracking) and perform data validation to ensure accuracy, completeness, and reliability.

• Performance and Quality: Monitor and improve existing data workflows to reduce latency and improve accuracy. Apply data governance and validation practices under the guidance of senior engineers to keep data compliant with EHS standards and manufacturing requirements.

• Collaboration and Support: Work with Paint Shop teams (supervisors, engineers, and analysts) to understand their needs and translate them into data solutions. Support data-related projects such as dashboards for cycle time tracking or automated reporting for production metrics.

• Problem-Solving and Growth: Contribute to initiatives that apply advanced technologies, such as machine learning for anomaly detection in paint defects or IoT data feeds. Help maintain and extend the iSVS (Internal Surface Vision System) for defect classification. Surface opportunities for process improvements, such as reducing paint material waste through data insights, and grow your technical depth across the stack.

• Documentation: Keep clear documentation of the pipelines and processes you own. Follow Tesla's safety protocols, data privacy standards (e.g., GDPR), and sustainability goals.

What You'll Bring

• Education: Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field (or equivalent practical experience).

• Experience: 2+ years of experience in data engineering or a closely related role. Exposure to manufacturing, automotive, or industrial data is a plus.

• Proficiency in Python (Java or Scala a plus).

• Working experience with data pipelines and at least one big data or streaming tool (e.g., Apache Spark, Kafka) or a willingness to learn.

• Solid SQL skills (e.g., PostgreSQL, MySQL); exposure to NoSQL and orchestration tools (e.g., Airflow) is a plus.

• Familiarity with API integrations and version control (Git).

• Soft Skills: Good problem-solving ability, clear communication with technical and non-technical colleagues, and the ability to work well in a dynamic, high-pressure environment.

• Other: Willingness to work in a manufacturing setting with occasional shift flexibility. Must pass Tesla's background check and safety training.

Preferred Qualifications

• Exposure to MES systems, IoT platforms, or data visualization tools (Tableau/Power BI).

• Basic understanding of manufacturing processes, such as paint application, quality inspection, or EHS compliance.

• Interest in machine learning or AI for predictive analytics in production settings, including systems like iSVS.

, Tesla

Enterprises are adopting AI faster than they can govern it — and they are looking for a partner who can do two things at once: speak credibly about AI trust, governance, and security, and actually build. The Forward Deployed Engineer (AI) is that partner.

You are the technical face of AvePoint inside client organizations: equally comfortable whiteboarding AI trust and governance concepts with a CISO, translating a business problem into a scoped AI build project, and writing the first working prototype yourself. You embed with clients, ship real outcomes, and own the engagement end to end.

This is not a pre-sales role with a demo script, and not a back-office delivery role. It is the engagement model pioneered by leading AI companies for their strategic enterprise customers: a senior engineer deployed forward, with the autonomy to own the problem from first workshop to production.

What you'll doAdvise on AI trust and governance.

Lead workshops that help clients understand and take control of their AI landscape — agents, copilots, models, and the data behind them, including the shadow AI they didn't know about. Explain AI governance, security posture, and resilience concepts credibly to both technical teams and executives. Guide clients through obligations such as the EU AI Act, NIS2, and ISO 42001, and help them stand up practical operating models: AI inventories, approval workflows, risk classification, and audit evidence.

Scope and shape AI build projects.

Sit with business stakeholders to understand the underlying need behind "we want AI for X." Identify the highest-value use cases, define success criteria, and translate ambiguous requirements into concrete, estimable technical scopes — architecture outlines, data and integration requirements, delivery phases, effort and risk assessments. Write statements of work that engineering teams can actually deliver and clients can actually sign.

Build and deliver.

Develop prototypes and production components for client AI solutions: agent workflows, RAG pipelines, LLM integrations (Azure OpenAI, AWS Bedrock, Google Vertex, Anthropic), MCP-based tool integrations, and the governance and security controls around them. Deliver custom adapters and local tooling for regulated, cloud-restricted, or air-gapped environments where standard SaaS approaches cannot go.

Own the relationship through delivery.

Act as the trusted technical advisor from first workshop through go-live: run enablement sessions, support adoption, troubleshoot in production, and expand the engagement where you see genuine value for the client.

What we're looking forMust-haves

• 5+ years in software engineering, solutions architecture, or technical consulting, with at least 2 years hands-on with modern AI/LLM systems in real projects (not only experimentation).
• Practical experience building with LLM APIs and frameworks (e.g., Azure OpenAI, Bedrock, Vertex, LangChain, Semantic Kernel) and patterns such as RAG, agentic workflows, and tool/function calling.
• Machine Learning Expertise:
  Hands-on machine learning experience spanning model development, evaluation, deployment, and operationalization, with a focus on enterprise AI solutions, predictive analytics, and scalable MLOps practices.
• Strong programming skills in Python and/or C#/TypeScript, plus working fluency with at least one major cloud platform (Azure, AWS, or GCP), including identity, networking, and data services.
• Demonstrated ability to scope technical projects from ambiguous business requirements: you can run a requirements workshop, challenge assumptions constructively, and produce a credible plan with phases, estimates, and risks.
• Excellent communication in front of senior stakeholders — you can explain why AI governance matters to a board member and debate vector database trade-offs with a platform engineer in the same meeting.
• Willingness to travel to client sites and to operate with high autonomy in ambiguous, fast-moving engagements.

Strong pluses

• Working knowledge of AI governance and compliance frameworks: EU AI Act, NIS2, ISO/IEC 42001, NIST AI RMF, or Gartner's AI TRiSM model.
• Experience with AI security topics: prompt injection, data leakage, agent permissioning, model and data security posture (AI-SPM/DSPM concepts).
• Familiarity with the Model Context Protocol (MCP), agent runtimes, or vector databases (e.g., Pinecone, Milvus, Weaviate, Chroma).
• Background in enterprise data governance, security, backup/resilience, or the Microsoft 365 / multi-cloud ecosystem where AvePoint operates.
• Experience delivering into regulated industries (public sector, defense, financial services, healthcare) or air-gapped/sovereign environments.
• Prior experience in a forward-deployed, embedded consulting, or customer-facing engineering role.
• Additional languages relevant to your region's client base.

How we'll measure success

Within your first 6–12 months, you will have led AI discovery and governance workshops for multiple enterprise clients, scoped and won at least one significant AI build or governance engagement, and delivered working software into a client environment. Above all: clients ask for you by name.

Why this role, why now

AI adoption has outrun enterprise control, and regulators have noticed. Every large organization now needs to see, govern, secure, and sustain its AI estate — and most need a partner who can both advise and build. As an FDE at AvePoint you will help define this engagement model from the ground floor, work at the frontier of agentic AI and AI trust, and do it with two decades of enterprise data governance and resilience expertise behind you.

 

Any personal data you share with us during the application process will be processed strictly in compliance with applicable data protection laws and our Privacy Notice.

The Run & Grow Tribe of Tribes powers the systems, insights, and experiences that keep millions of merchants engaged, successful, and growing with SumUp across every market we operate in. We're at a genuine inflection point in how we use data, moving from fragmented pipelines to a world-class data foundation built on stable business domains, trusted metrics, and AI-ready data products. This is a greenfield opportunity to shape how data is owned, defined, and built at scale, and as our Analytics Engineer, you'll be the connective tissue that makes that vision real.

What you'll do

• Partner with squads across the tribe on event design and data contracts, maintaining staging pipelines, applying modelling conventions, and keeping domain outputs consistent, tested, and discoverable
• Model key business domains, including merchant activity, product adoption, lifecycle events, and risk scoring, building well-documented, quality-assured data products that serve as the trusted source of truth across the organisation
• Build and maintain the insights layer on top of governed domains, producing reusable KPI models, funnels, cohorts, and segmentations that Product, Commercial, and AI teams can self-serve with confidence
• Implement technical improvements including incremental processing strategies, performance optimisations, and scalable data architecture to support growing data volumes
• Contribute to SumUp's broader data domain strategy, helping establish durable ownership, consistent definitions, and a shared catalogue of data products that unlock self-serve analytics and AI at scale

You'll be great for this role if…

• Strong, proven experience in analytics engineering or data engineering, with a track record of building and maintaining production data systems
• Expert-level SQL skills for complex transformations and query optimisation, with hands-on experience building layered data models in a modern data warehouse or lakehouse (e.g. Snowflake, Iceberg) and solid command of dbt, including testing, documentation, and modelling conventions
• Ability to think in terms of business domains, not just tables, translating complex business logic into clean, durable, and reusable data models across entities, events, states, and rules
• Comfort working across squads with Product Managers, Engineers, Analysts, and Data Scientists, contributing to data design conversations and helping teams treat data as a first-class deliverable
• Deep care for data quality, trust, and discoverability, building models others can rely on, with a proactive mindset around contracts, freshness, observability, and failure scenarios

Why you should join SumUp

• 🌎 Opportunity to work with SumUppers globally on large-scale fintech products used by millions of businesses worldwide, from our Berlin office. This involves an office-first setup
• 🌈 Commitment to Diversity and Inclusion: be part of a workplace that values and promotes diversity, fostering an inclusive environment where everyone's perspectives are respected and embraced
• 🚀 Enrolment onto our Virtual Stock Option programme: you will own a stake in SumUp's future success
• 📚 A dedicated annual L&D budget of €2000 for your individual development, which can be used to attend conferences and/or advance your career through further education
• 💶 A corporate pension scheme where we match up to 20% of your contributions
• 🏖️ Generous time off: enjoy 28 days of paid leave plus public holidays and special leave days
• 🏋️ Numerous other benefits such as Urban Sports Club subsidy, Kita placement assistance, subsidised office lunches
• 🌴 Break4me: 1-month sabbatical after 3 years of service
• 🔗 Referral Bonus: earn additional rewards by referring talented individuals to join the SumUp team

About SumUp
Be empowered to do more that matters.

At SumUp, we're on a mission to empower small businesses across the globe by providing simple and affordable tools that allow them to thrive. Today, over 4 million businesses in 37 markets rely on SumUp as their financial partner to manage payments, finance and customer relationships.

Our commitment to small businesses is reflected in our diverse team of over 3,000 SumUppers from over 90 nationalities, united by global collaboration and an innovative mindset. Our core values lay the foundation for who we are and what we stand for, shaping our work culture and driving our success. We foster inclusivity and a continuous learning culture, providing a safe space for personal and professional growth. Our differences make us unique and strong as we strive to create an environment where everyone belongs and feels supported, no matter how they identify.

SumUp is proud to be an Equal Employment Opportunity employer, actively seeking and embracing diversity in our workforce. We don't make hiring or employment decisions based on race, colour, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age or any other basis protected by applicable laws or prohibited by company policy. Our commitment extends beyond recruitment to creating a safe and respectful workplace where harassment of any form is strictly prohibited. Discover more about our culture and opportunities on our careers website, and follow our journey on LinkedIn, Instagram, and TikTok.

Job Application Tip
We recognise that candidates feel they need to meet 100% of the job criteria in order to apply for a job. Please note that this is only a guide. If you don’t tick every box, it’s ok too because it means you have room to learn and develop your career at SumUp.

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As a Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data.

This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.

The Impact You Will Have

• Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
• Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
• Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
• Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What We Look For

• 6+ years experience in data engineering, data platforms & analytics, or software engineering
• Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps, ML/AI models and AI APIs
• Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
• Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
• Documentation and white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range
• Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.