Solution Engineer - Data & AI
Design and implement integration projects and scalable API strategies within complex enterprise architectures. Develop AI-supported end-to-end processes and establish best practices for intelligent automation.
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Design and implement integration projects and scalable API strategies within complex enterprise architectures. Develop AI-supported end-to-end processes and establish best practices for intelligent automation.
Architect and lead the evolution of an AI-augmented quality engineering platform for cloud-native broadband systems. Drive autonomous testing strategies and integrate QA into DevOps/MLOps pipelines to ensure high reliability and performance.
Design and implement a multi-agent AI architecture for an automated video production system. Orchestrate complex workflows using n8n to integrate multimodal tools for scripting, editing, and synthesis.
Lead the design, training, and deployment of ML models and autonomy architectures for lunar surface and in-space operations. Manage a focused team of engineers to build simulation pipelines and integrate AI capabilities into Blue Origin's space systems.
Design and implement AI/GenAI features and agent-based workflows using frameworks like LangChain and Azure AI Foundry. Develop full-stack applications and APIs while collaborating with cross-functional teams to optimize AI models and pipelines.
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Lead the technical architecture of the agent-readable Shop Builder platform, defining APIs and interface contracts for developers and AI agents. Design and deliver critical tooling including MCP servers, CLIs, and evaluation harnesses to enable end-to-end storefront operation.
Design and deploy enterprise-grade software and a custom ERP platform using AI-assisted development tools. Translate complex business processes into scalable applications and automate internal workflows to improve operational efficiency.
Design and develop edge machine learning systems and scalable infrastructure to improve the autonomy and safety of construction robots. Optimize computer vision and sensor fusion models while integrating cloud-based AI tools into the autonomy stack.
Design and develop geometry processing and simulation algorithms for engineering applications. Build services for processing 2D/3D engineering data and implement post-training workflows for machine learning models.
Own and operate GPU and accelerator clusters to power model training, inference, and experimentation. Design and optimize scalable, cost-efficient compute infrastructure and inference pipelines to reduce dependency on external providers.
Design and implement the AI Factory Cloud platform, focusing on automation, optimization, and the lifecycle of CI/CD pipelines. Provide technical leadership and mentorship to co-workers while coordinating activities across related technologies.
The Forward Deployed Engineer will partner with business stakeholders to rapidly build and deploy automation and AI-driven solutions. This role involves full-stack engineering, including data pipelining, backend development, and the creation of dashboards to solve complex business problems.
You will develop and evolve the technical backbone of the company's Conversational AI platform, including voicebot and chatbot systems. You will also design RAG architectures and optimize LLM integrations for performance, latency, and cost in production environments.
Collaborate with cross-functional teams to design, develop, and deploy scalable AI and machine learning products for the utility industry. Build reusable Python packages, design AI system components, and implement monitoring frameworks to ensure model performance and fairness.
The role involves building observability, automation, and AIOps foundations while participating in root cause analysis and support insights. You will also prototype lightweight agents and optimize workflows within incident management tooling.
Research, design, and develop comprehensive AI security labs and immersive learning experiences for the TryHackMe platform. Collaborate with the content engineering team to translate complex AI security research into actionable, practical training scenarios.
The main task involves designing and building applications using Python, while also supporting component design, development, maintenance, and defining structured practices for building and deployment. Responsibilities extend to designing data storage solutions, optimizing application performance, gathering user feedback, and assisting with client requirement analysis.
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The engineer will act as the subject matter expert, modeling customer facilities for AI ingestion using Phaidra's platform and collaborating with Data Scientists to define product requirements based on customer needs. They will also work to ensure automated tools enable scaling the solution across thousands of customers.
The role involves contributing to AI model training by curating code examples, providing precise solutions, and offering meticulous corrections in specialized programming languages. Responsibilities also include evaluating and refining AI-generated code to ensure adherence to industry standards for efficiency, scalability, and reliability.
Design and implement core platform services exposed through high-quality APIs and SDKs for a unified data and AI/ML model development platform. Partner closely with AI/ML researchers, data engineers, and product teams to deliver a paved-path developer experience.
The AWS Engineer will design, build, and maintain scalable data pipelines and analytics platforms on AWS. This includes transforming raw data into analytics-ready datasets and ensuring data quality and compliance.
The main task involves designing and building applications using Python, while also supporting component design, development, maintenance, and taking responsibility for technical quality standards. Responsibilities may also include defining structured practices, designing data storage solutions, optimizing performance, and collaborating with clients and technical leaders on project execution.
As a Senior Platform Engineer, you will design and deploy scalable multi-cloud architectures while automating infrastructure processes. You will also translate business requirements into technical solutions and build robust delivery pipelines.
Design and implement multi-stage matching systems for compatibility scoring and personalization. Collaborate cross-functionally to integrate AI seamlessly into the user experience.
Lead the end-to-end technical delivery of complex AI solutions, ensuring successful deployment and measurable business impact. Design and develop bespoke solutions leveraging the Agentforce platform and other cutting-edge technologies.
Design, implement, and maintain CI/CD pipelines for AI and analytics solutions. Collaborate with AI Engineers and Solution Architects to develop platforms and operational frameworks.
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You will set the technical direction for production AI/ML systems, owning the full lifecycle from model design to deployment and optimization. You will also partner with cross-functional stakeholders to shape strategy and ensure the delivery of safe, scalable, and high-impact health AI solutions.
You will architect and own the marketing data infrastructure, including ETL/ELT pipelines and Databricks Gold Layer tables to power self-serve analytics. Additionally, you will lead complex cross-team initiatives and drive the strategic use of AI to build reliable data products and automated workflows.
The Growth Engineer will own and execute an integrated search-driven strategy across SEO, SEM, GEO, and GEM to generate qualified leads and revenue. This involves hands-on campaign management, content optimization, and building attribution models to measure performance.
Build and maintain reusable AI tooling, RAG-based knowledge systems, and automated workflows to improve engineering productivity. Define and monitor the reliability, security, and cost-effectiveness of internal AI platforms.
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