Role Description Cityblock is putting AI directly into the hands of the care teams and members we serve. You are a full-stack product engineer who takes an AI-native idea from a rough prototype to a feature running in production, in front of real clinical users, and you contribute to the prototyping loop that lets product and design move at that speed. Most of the value of AI in our product is still undiscovered. Your job is to shorten the distance between an idea and something people can actually use, and then to productionize effective use of AI into features that hold up in a regulated healthcare product. Reporting into the Product Engineering org, this role covers system design, including the LLM/SDK integration underneath, the evals and golden datasets that tell you whether it's working, and the UX. You embed with product, design, and work with clinical operations. Because these features run in a regulated healthcare product in front of real members and care teams, you help decide where AI acts on its own, where it stays advisory with a human in the loop, and how we prove a feature is safe to trust, designing for compliance from the start. Responsibilities - Implement full-stack feature work that integrates LLM APIs and SDKs into member- and care-team-facing product surfaces. - Own features end to end: system design, model/SDK integration, evals, and the UX that determines whether the feature is actually trusted and used. - Build observability and evals alongside the feature, so quality can be measured and then improved. - Apply and help improve the team's prototyping loop, eval discipline, and quality bar through the work you ship. - Put prototypes in front of real users early, learn from what breaks, and harden the ones worth keeping into production. - Bring an honest read of what's feasible back to product and design, so the roadmap reflects reality. - Work with product management, design, and clinical operations to find and understand the high-value AI opportunities behind the features you build. - Partner with the data organization for the grounded, trustworthy context your features depend on. Qualifications - 4+ years of experience as an engineer. - You are a strong full-stack product engineer who ships. You solve problems by building working software. - Experience integrating LLM APIs or SDKs into a shipped product, or closely related production experience you can build on. - Strong product sense: you care about whether people use your products and whether they provide measurable value. - Comfort owning ambiguity by taking a well-scoped, high-value idea and turning it into something real, with decreasing guidance over time. - Experience building evals or quality measurement for AI features, or the clear instinct that you need to. - Fluent daily use of AI assistants for engineering, with a clear sense of when to trust them and when not to. - Drawn to mission-oriented work, and comfortable partnering with clinical and design experts whose expertise differs from yours. Nice to Have - A CS degree or equivalent. - Prior work in a regulated or compliance-heavy environment (HIPAA, SOC 2, or similar). - Experience building AI-native product features from scratch, including the evals around them. - Design sensibility strong enough to prototype UX yourself. - Exposure to clinical operations or working alongside clinical staff as end users. - Hands-on with retrieval-augmented generation (RAG): embeddings, vector search, and grounding LLM output in trusted context. - Familiarity with agentic patterns including tool/function calling, structured outputs, and multi-step orchestration. - Experience with LLM eval and observability tooling (e.g., Braintrust, LangSmith) and LLM-as-judge techniques. - Comfort in a modern TypeScript/Node/React stack, including streaming and latency-sensitive LLM UX. Benefits - This role is eligible for health insurance, life insurance, retirement benefits, participation in the company’s equity program, paid time off, including vacation and sick leave. Salary Information The expected salary range for this position is: $139,000.00 - $183,000.00 Annual. Diversity and Inclusion Cityblock values diversity as a core tenet of the work we do and the populations we serve. We are an equal opportunity employer, indiscriminate of race, religion, ethnicity, national origin, citizenship, gender, gender identity, sexual orientation, age, veteran status, disability, genetic information, or any other protected characteristic.

Role Description We are seeking an AI Engineer – Data & AI Platform to architect, build, and operationalize scalable generative AI and machine learning solutions across Snowflake, Databricks, and modern MLOps ecosystems. This role will partner with data scientists, ML engineers, and platform teams to design and deploy end-to-end AI/ML pipelines, advance AI integration, and ensure production-grade reliability for AI-driven products. The ideal candidate has 8+ years of experience in AI/ML engineering, with deep expertise in generative AI deployment, API-based AI services, large-scale data processing, and AI lifecycle management. The AI Engineer will not only deliver hands-on technical solutions but also set technical direction, mentor other engineers, and drive innovation across Teladoc's AI platforms. Essential Duties and Responsibilities - Operationalize GenAI and LLM applications, leveraging RAG (retrieval-augmented generation), vector search, prompt engineering, agentic AI, and MCP (Model Context Protocol). - Lead the design, development, and deployment of production-grade LLM and ML pipelines, including data transformation, feature engineering, training, tuning, and serving. - Architect scalable data and AI workflows on Snowflake, Databricks, and Azure ML, integrating AI models with modern data lakehouse platforms. - Build and maintain API-based AI services (FastAPI, Flask), enabling secure, performant, and reliable model access at scale. - Define and implement CI/CD pipelines for GenAI and ML services, using GitHub Actions/Azure DevOps, MLFlow, and container orchestration (Kubernetes, Docker). - Develop and enforce MLOps/LLMOps best practices, including experiment tracking, model versioning, observability, and governance. - Mentor ML engineers and data scientists on engineering rigor, scalable design, and production-readiness. - Partner with cross-functional teams to integrate AI services into products, ensuring security, compliance, and resilience in regulated healthcare environments. - Troubleshoot production AI systems, analyzing inference latency, drift, and performance issues, and implementing preventive solutions. - Document and communicate architecture patterns, operational standards, and AI development frameworks across the organization. Qualifications - Bachelor's degree in Computer Science, Engineering, Machine Learning, or a related field; equivalent work experience is acceptable. - 8+ years of experience in AI/ML engineering roles, with proven success in architecting and scaling production LLM/GenAI and ML systems. - Experience deploying LLM and GenAI solutions including RAG, vector database integration, and agentic/tool‑augmented LLM systems (LangChain, MCP, or similar frameworks). - Experience with Snowflake or Databricks, using one or both as core platforms for data processing or AI/ML workloads. - Proven track record in MLOps/LLMOps, including CI/CD pipeline automation, model serving, monitoring, and governance, using modern AI infrastructure tools such as Docker, Kubernetes, Azure ML, MLflow, and Terraform. - Proficiency in Python and SQL, with experience processing high‑volume datasets using big‑data tools such as Spark or equivalent distributed systems. - Ability to collaborate in cross-disciplinary teams (engineering, product, compliance, security) and deliver impact in regulated industries. Bonus Qualifications - Excellent communication skills to articulate complex GenAI/ML concepts to diverse audiences. - Strong leadership and mentorship abilities, fostering technical growth across teams. - Understanding of API-driven AI development, including Python-based API frameworks (FastAPI, Flask) or equivalent experience working with API development workflows. - Certifications in Snowflake, Databricks, Azure ML, or AI/ML platforms preferred. - Experience in healthcare AI applications and regulated AI deployment. Requirements - The base salary range for this position is $200,000 - $230,000. - This position is eligible for a performance bonus and benefits (subject to eligibility requirements). - We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. - All time off must be approved by your manager prior to use. - You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. - This applies to full-time positions only. - If you are applying for a part-time role, your recruiter can provide additional details. Benefits - As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. - Applicants who falsify information will be disqualified. - Teladoc Health will not sponsor or transfer employment work visas for this position. - Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Role Description Design, develop, implement, and operate enterprise solutions based on Generative Artificial Intelligence, Machine Learning, and Intelligent Automation on Microsoft Azure. You will be responsible for building scalable AI components, integrating foundational models and cognitive services with enterprise applications, and ensuring the secure, efficient, and governed operation of solutions in production environments. Main Responsibilities - AI Solution Development - Design and implement applications based on Generative AI and Large Language Models (LLM). - Build enterprise copilots, virtual assistants, and intelligent agents. - Develop semantic search and Retrieval-Augmented Generation (RAG) solutions. - Implement reasoning, orchestration, and automation mechanisms using AI agents. - Integrate AI services with enterprise applications, APIs, and data platforms. - Data Engineering for AI - Design data ingestion, transformation, and enrichment pipelines. - Implement knowledge indexing and vectorization strategies. - Manage structured and unstructured knowledge repositories. - Ensure the quality, consistency, and traceability of data used by AI models. - Implementation and Operation - Deploy solutions using Azure managed services. - Implement LLMOps, MLOps, and DevSecOps best practices. - Monitor the performance, costs, accuracy, and adoption of solutions. - Manage versions of AI prompts, models, and components. - Quality and Security - Apply Responsible AI principles. - Implement security and data protection controls. - Ensure compliance with business and regulatory standards. - Participate in architecture and technical quality reviews. Required Technology Stack - Azure AI & GenAI - Azure OpenAI Service - Azure AI Foundry - Azure AI Search - Azure AI Content Safety - Azure Machine Learning - Azure AI Document Intelligence - Azure AI Language Services - Azure Cognitive Services - Application Development - Python - C# - .NET 8 - REST APIs - FastAPI - ASP.NET Core - JavaScript/TypeScript - AI Frameworks - Semantic Kernel - LangChain - LangGraph - AutoGen - CrewAI - OpenAI SDK - Azure AI SDK Company Description Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Role Description SG Lottery is looking for a self-motivated, experienced Technical Operations Engineer to join a Technical Operations team that supports our lottery solutions. Our team works closely with our Infrastructure, Development, and testing teams to identify issues while also suggesting and implementing corrective actions. You will work on both standard support issues - ensuring a smooth operation of our platform, and on project specific work including new product releases, enhancements, and upgrades of the product for existing and new customers. Our environments run predominantly Windows Server and SQL Server. IIS and WildFly are used throughout environments. There is some Ubuntu server support required. Job Duties / Key Accountabilities - Provides tier 2 support for the lottery platforms. - Support new customer implementations as well as support and maintain existing customer solutions. - Triage, troubleshoot, and resolve issues with system availability, latency, or performance. - Ensure system capacity is being monitored and considered in planning. - Identify and address system security concerns. - Ensure Incidents assigned to the team are being managed within agreed SLAs. - Define, refine, and track Service Level Objectives. - Setup and maintain monitoring of system and ensure all alarms are documented in up-to-date Knowledge Base Articles. - Create and maintain support documentation and procedures. - Participate in a 24x7x365 on-call rotation. Qualifications - 5+ years of experience working in a system administration role in a high demand, highly available environment. - SME level knowledge of Microsoft Windows Server with a focus on system administration, configuration, and diagnostics. - Basic skills working with Ubuntu Linux; familiarity with command line, bash scripting, basic configurations, etc. - Solid understanding of SQL Server database engine including configuration, data analysis, and replications including AlwaysOn Availability Groups. - Working knowledge of common protocols such as SFTP, SSH, SMTP, DNS, and HTTP/S. - Familiarity with web certificate management. - Proven communication, presentation, and documentation skills. - Strong interpersonal and problem-solving skills. - Time management and prioritization skills. Requirements - SME level knowledge of Active Directory and domain administration. - Familiarity with WildFly and Java based application. - Scripting skills using PowerShell, bash, or Python. - Experience with WAF solutions such as Imperva or Cloudflare. - Basic PostgreSQL administration knowledge. - Experience with automation tools such as Ansible. Education - Bachelor’s degree in computer sciences with 3+ years’ experience with Windows administration. Company Description SG is an Equal Opportunity Employer and does not discriminate against applicants due to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. If you’d like more information about your equal employment opportunity rights as an applicant under the law, please click here for EEOC Poster.