Zencore

• Serve as Zencore’s senior-most technical authority on the practical application of advanced artificial intelligence and machine learning. • Partner with the sales and business development teams in a pre-sales capacity to scope opportunities, design solutions for proposals, and act as the senior technical voice in client pitches. • Lead the architecture and design of sophisticated, secure, and scalable AI solutions for our clients, moving beyond standard API integrations to create genuine competitive advantages. • Collaborate closely with Cloud & Data Architects to guarantee the design and deployment of comprehensive client solutions. • Address the growing demand for private, data-sovereign AI by designing systems that meet strict GDPR and data privacy requirements. Strive for model explainability and bias mitigation, ensuring solutions adhere to ethical standards and safety guardrails. • Architect solutions for hosting, fine-tuning, and optimizing both proprietary (e.g., Gemini, Claude) and open-source (e.g., Llama, Mistral) models on hyperscaler platforms. • Lead clients in selecting optimal cloud-native technologies, prioritizing Google Cloud solutions for deploying and scaling production-grade agentic systems. • Guide and mentor customers and Zencore's engineering teams on advanced topics, establishing best practices for high-performance training (PyTorch, JAX, TPUs), efficient model serving (vLLM), and complex agentic systems (LangGraph, Langchain, Google ADK). • Devise the financial architecture of AI solutions by performing ROI analysis and implementing cost-optimization strategies to ensure large-scale deployments remain economically sustainable for customers. • Act as an external thought leader, contributing to the Zencore brand through blog posts, conference presentations, and community engagement. • Act as a "player-coach," providing hands-on leadership and fostering a culture of deep technical excellence in AI/ML.

• Build and grow executive relationships with enterprise customers. Influence long-term strategic direction and serve as a business partner. • Present to C-level executives in corporate and global customers. • Lead account strategy and work collaboratively with Google Sales and Customer Engineering team to identify new opportunities. • Understand each customer’s technology footprint, strategic growth plans and business drivers, technology strategy and business landscape. • Drive business development, forecast accurately, and achieve strategic goals by leading customers through the entire business process.

• The Sales Director position is focused on growing the professional services and managed services business by building relationships with CEOs, CTOs and other company executives. • You will be responsible for strategy, execution and assembling a team that will focus on aligning the Zencore offerings with business and technology initiatives and partnering with the Google Cloud Select and Enterprise sales teams to drive revenue into strategic accounts. • Note: Even though it is remote, this individual must be located in Northern Europe

• As a member of our Data Engineering team, you will be working with fast-paced innovative companies, leveraging Cloud as the key driver of their transformation. • They will look at you as their trusted advisor, someone they can rely on and who will be there to help them along their journey on Google Cloud. • You will be expected to cover a large spectrum of technology topics like ETL/ELT, Data Warehousing, Distributed Data Processing, and Streaming Data systems. • NOTE: This role is a 6 month Contract w/ potential of extension

• Providing strategic guidance and facilitating technology decisions • Executing projects using a collaborative, co-development style • Supporting cross-cloud migration work focused on core cloud infrastructure, managed services, networking, Kubernetes, databases, and CI/CD tooling across enterprise environments

• Design, build, and optimize large-scale distributed data pipelines using Apache Beam / Google Cloud Dataflow, Apache Spark, or Apache Flink. • Develop ETL/ELT workflows on GCP integrating multiple structured and unstructured data sources. • Address schema, type conversion, and performance optimization challenges when migrating data warehouses to BigQuery. • Implement observability, monitoring, logging, and error-handling within pipelines. • Collaborate with Data Analysts to integrate validation rules, QA checks, and automated testing into the pipeline lifecycle. • Support large-scale data migrations and performance tuning for high-volume workloads.

• Design, implement, and manage cloud infrastructure in Google Cloud • Migrate applications from on-premise environments or other cloud providers (AWS, Azure) to GCP • Work on application modernization using containers, Kubernetes, and serverless technologies • Troubleshoot complex systems across infrastructure, networking, databases, and applications • Collaborate directly with customer teams to guide architecture and technical decisions • Build automation and infrastructure as code using modern tooling • Act as a trusted technical advisor, bringing clarity to ambiguous problems

• This role is for individuals that have a passion for being builders. • The Sales Director position is focused on growing the professional services and managed services business by building relationships with CEOs, CTOs and other company executives. • You will be responsible for strategy, execution and assembling a team that will focus on aligning the Zencore offerings with business and technology initiatives and partnering with the Google Cloud Select and Enterprise sales teams to drive revenue into strategic accounts.

• Serve as Zencore’s senior-most technical authority on the practical application of advanced artificial intelligence and machine learning. • Partner with the sales and business development teams in a pre-sales capacity to scope opportunities, design solutions for proposals, and act as the senior technical voice in client pitches. • Lead the architecture and design of sophisticated, secure, and scalable AI solutions for our clients, moving beyond standard API integrations to create genuine competitive advantages. • Collaborate closely with Cloud & Data Architects to guarantee the design and deployment of comprehensive client solutions. • Address the growing European demand for private, data-sovereign AI by designing systems that meet strict GDPR and data privacy requirements. Strive for model explainability and bias mitigation, ensuring solutions adhere to ethical standards and European safety guardrails. • Architect solutions for hosting, fine-tuning, and optimizing both proprietary (e.g., Gemini, Claude) and open-source (e.g., Llama, Mistral) models on hyperscaler platforms. • Lead clients in selecting optimal cloud-native technologies, prioritizing Google Cloud solutions for deploying and scaling production-grade agentic systems. • Guide and mentor customers and Zencore's engineering teams on advanced topics, establishing best practices for high-performance training (PyTorch, JAX, TPUs), efficient model serving (vLLM), and complex agentic systems (LangGraph, Langchain, Google ADK). • Devise the financial architecture of AI solutions by performing ROI analysis and implementing cost-optimization strategies to ensure large-scale deployments remain economically sustainable for customers. • Act as an external thought leader, contributing to the Zencore brand through blog posts, conference presentations, and community engagement. • Act as a "player-coach," providing hands-on leadership and fostering a culture of deep technical excellence in AI/ML.

• Design and execute technical processes to migrate data from Oracle (Clarity) to Google BigQuery. • Handle complex schema mappings, specifically resolving incompatibilities between Oracle data types and BigQuery (e.g., handling timestamps, numerics, and character sets). • Troubleshoot pipeline failures related to hardware latency and legacy infrastructure constraints. • Develop automated SQL scripts and testing frameworks to validate data replication accuracy at scale. • Perform deep-dive root cause analysis on data inconsistencies, distinguishing between genuine data errors and artifacts of the conversion process. • Create technical documentation for data lineage and conversion logic. • Optimize SQL queries for performance within the BigQuery environment to manage costs and reduce latency. • Collaborate with Data Analysts to verify business logic and ensure the migrated data meets clinical reporting standards.