... such as Databricks, Snowflake, or BigQuery, is a plus. * Spanish proficiency is considered an ... Fully remote working environment with the flexibility to work from anywhere. * One-time home office ...
... such as Databricks, Snowflake, or BigQuery, is a plus. * Spanish proficiency is considered an ... Fully remote working environment with the flexibility to work from anywhere. * One-time home office ...
... Databricks, and Google Cloud, and a major fundraise ahead, Obsidian is scaling rapidly toward ... This is a 100% remote role, but you must be based within the Central region (Illinois, Indiana ...
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... Databricks, and Google Cloud, and a major fundraise ahead, Obsidian is scaling rapidly toward ... This is a 100% remote role, but you must be based within the Central region (Illinois, Indiana ...
Remote Databricks information
What is a remote Databricks engineer?
Remote Databricks jobs are positions that involve working with the Databricks data analytics platform from a location outside of a traditional office, typically from home or another remote setting. These roles often focus on developing data pipelines, analyzing big data, building machine learning models, or managing cloud infrastructure using Databricks. Employees use collaboration tools and cloud-based environments to connect with their teams and access the Databricks platform securely. Remote Databricks jobs may be available for data engineers, data scientists, machine learning engineers, and DevOps professionals. The flexibility of remote work allows professionals to collaborate with global teams while leveraging Databricks’ powerful data processing and analytics capabilities.
How does a remote Databricks engineer typically collaborate with cross-functional teams?
As a remote Databricks engineer, you will frequently work with data scientists, analysts, and other engineers through virtual collaboration tools such as Slack, Jira, and Zoom. Regular stand-up meetings, code reviews, and shared documentation platforms help maintain alignment across distributed teams. You'll often contribute to shared Databricks notebooks and participate in sprint planning to ensure data pipelines and analytics workflows meet business requirements. Effective communication and proactive documentation are key to successful remote collaboration in this role.
What are the key skills and qualifications needed to thrive as a remote Databricks engineer?
To thrive as a Remote Databricks Engineer, you need a strong background in data engineering, cloud computing (especially Azure or AWS), and proficiency in languages like Python or Scala, often supported by a degree in computer science or a related field. Familiarity with Databricks platform tools, Spark, SQL, and relevant certifications such as Databricks Certified Data Engineer Associate are typically required. Strong problem-solving, communication, and self-motivation skills help you excel in remote and collaborative data-driven environments. These skills are essential for efficiently designing scalable data solutions and collaborating virtually to drive business value.
What are popular job titles related to Remote Databricks jobs in Missouri?
For Remote Databricks jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Remote Databricks jobs in Missouri look for?
The top searched job categories for Remote Databricks jobs in Missouri are:
Staff AI Engineer, Payments Intelligence
On-site, Remote
Jobgether
Full-time
Medical
Posted 9 days ago
Job description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Engineer, Payments Intelligence based in Netherlands.
As a Staff AI Engineer, you'll serve as a senior technical leader responsible for shaping the architecture and delivery of AI systems at the core of a global payments platform. You'll design and build production-grade AI agents, LLM pipelines, and intelligence products that solve complex payment and operational challenges. Your work will span agentic AI, conversational experiences, data intelligence, automation, evaluation, and AI safety. You'll operate in a highly technical, hands-on environment where reliability, scalability, latency, and responsible AI are critical. You'll collaborate closely with Product, Data Science, and senior engineering teams while mentoring other engineers and setting technical direction. This is an opportunity to have significant influence over how AI-powered payment products are designed, evaluated, and deployed globally.
Accountabilities
- Lead the architecture and technical direction of AI agents and Payments Intelligence systems, including multi-step agents, tool use, orchestration, memory, and retrieval-augmented generation (RAG).
- Design, develop, and productionize LLM and agentic AI systems engineered for reliability, scalability, low latency, and high-quality outcomes.
- Build intelligent conversational experiences capable of engaging customers dynamically across channels such as phone and messaging platforms, including multilingual interactions across 70+ languages.
- Develop AI solutions that retrieve payment information, recover revenue from failed transactions, automate internal operations, support customers, and generate actionable merchant insights.
- Establish rigorous approaches to AI evaluation, observability, safety, and guardrails to ensure reliable behavior in a compliance-sensitive, multi-market environment.
- Architect data and intelligence products that transform complex payment data into actionable insights for merchants.
- Define responsible practices for using AI-assisted development tools throughout the design, evaluation, and deployment lifecycle.
- Collaborate with Product, Data Science, and senior engineering stakeholders to deliver complex, cross-functional AI initiatives.
- Mentor engineers, promote strong engineering standards, and raise the technical bar for AI development across the organization.
- Own technical outcomes from system architecture through production deployment, with a focus on measurable impact and continuous improvement.
- Extensive software engineering experience with a proven track record of building and shipping production LLM or AI-agent systems.
- Deep expertise in agentic AI systems, including multi-step agents, tool use, orchestration, memory, and RAG.
- Strong LLM application development skills, including prompt engineering, evaluation, testing, and safety guardrails.
- Advanced Python skills for AI/ML development, combined with strong backend engineering capabilities in Go and/or Kotlin.
- Experience with model serving, LLM inference, and cloud infrastructure for running AI workloads in production, ideally with AWS or a comparable platform.
- Hands-on experience with AI evaluation and observability platforms such as LangFuse, LangSmith, Braintrust, or MLflow.
- Strong knowledge of automated testing and CI/CD practices for reliable production systems.
- Proven technical leadership experience, including mentoring engineers, defining technical vision, and delivering complex cross-team projects.
- Advanced written and spoken English proficiency.
- Experience with fine-tuning, RLHF, or model customization is advantageous.
- Familiarity with vector databases such as Pinecone, Weaviate, or FAISS and embedding-based retrieval.
- Experience building agent workflows using MCP servers or modern agent frameworks.
- Knowledge of conversational AI, speech-to-text, text-to-speech, and multilingual AI systems is a plus.
- Previous experience in payments, fintech, or another highly regulated environment is preferred.
- Experience operating multi-tenant AI platforms or managing GPU and AI resources at scale is beneficial.
- Familiarity with data pipelines and orchestration tools such as Airflow or Prefect, and data warehouses such as Databricks, Snowflake, or BigQuery, is a plus.
- Spanish proficiency is considered an additional advantage.
- Strong ownership, curiosity, problem-solving ability, and a hands-on approach to technical leadership.
- Competitive compensation.
- Fully remote working environment with the flexibility to work from anywhere.
- One-time home office allowance to help you create an effective workspace.
- Work equipment provided.
- Stock options.
- Health plan available wherever you are.
- Flexible days off.
- Language, professional, and personal development courses.
- Opportunity to work on advanced AI and agentic systems operating at significant production scale.
- International and distributed environment with collaboration across multiple markets and technical disciplines.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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