Role Description This role can be performed from any location within the United States. Be part of an Agile team moving at a very fast pace to ensure reliability, availability and performance of our next-generation segmentation and firewall platform. The team owns the full lifecycle of production services — from infrastructure architecture through deployment, observability, and operations. - As a Technical Leader, you will influence reliability architecture and drive operational excellence, collaborating with product management and field teams to ensure platform reliability. - Own the lifecycle of production services — deployment, monitoring, incident response, and capacity planning in a Linux-based multi-VM distributed systems environment. - Perform systems-level debugging and performance tuning in virtual machines, containers, and Kubernetes environments. - Build automation, tooling, and reliability frameworks in Python or Go, including database access layers and secrets storage, primarily using MongoDB, Vault, and Consul. - Operate and troubleshoot in Linux environments, including containers, virtual machines, and Kubernetes-orchestrated environments. - Manage and scale cloud infrastructure in AWS and GCP using Infrastructure as Code (IaC) tools such as Terraform. - Own and evolve CI/CD pipelines to enable rapid, safe deployment of changes in SaaS environments. - Conduct reviews, create runbooks, and lead post-incident learning across team members and the wider group, representing our platform in all forums. - Stay current with emerging technologies and industry trends in networking, security, cloud-native infrastructure, and related areas, while mentoring others. Qualifications - Bachelors + 8 years of related experience, or Masters + 6 years of related experience, or PhD + 3 years of related experience. - 6+ years in software development in Python or Go. - Experience with AWS, GCP, or other major cloud service providers, including deploying, managing, or troubleshooting cloud infrastructure and services in production environments. - Work experience across diverse infrastructure environments, including on-premise, cloud platforms, or hybrid environments. - Experience with Linux systems including networking. - Experience with bare metal servers or virtual machines (VMs). - Experience with containerized environments or Kubernetes-orchestrated systems. - Troubleshooting experience, to include cloud, on-premise or hybrid environments. Requirements - Experience designing and building Infrastructure as Code (IaC) with Terraform. - Experience in Kubernetes networking. - Strong background in testing high-performance computing, multi-threading, and low-latency systems. - Scripting, Ansible playbooks, and Jenkins experience. - Excellent verbal and written communication skills and professional presentation. Benefits - Medical, dental and vision insurance. - 401(k) plan with a Cisco matching contribution. - Paid parental leave. - Short and long-term disability coverage. - Basic life insurance. - 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees. - 1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco. - 16 days of paid vacation time per full calendar year for non-exempt employees. - Flexible vacation time off program for exempt employees. - 80 hours of sick time off provided on hire date and each January 1st thereafter. - Optional 10 paid days per full calendar year to volunteer. - Employees may be eligible to receive grants of Cisco restricted stock units.

Role Description We are looking for a Senior AI Platform Engineer with deep expertise in spec-driven AI SDLC, strong hands-on experience with AWS AI infrastructure (Bedrock, Bedrock Agents, Agent Core), and fluency across Java, TypeScript, and Python. You will champion a specification-first approach to AI development — translating product requirements into rigorous AI specs, building LLM-powered and agentic applications using Spring AI, and owning the full lifecycle from prototype through production on AWS. What a day in the life looks like: - Define AI feature specifications upfront — including acceptance criteria, evaluation metrics, prompt contracts, and expected behaviors. - Own end-to-end AI feature delivery across the full AI SDLC: spec definition, prototyping, development, evaluation, deployment, and production monitoring. - Build production-grade LLM and agentic AI applications using Spring AI — including RAG pipelines, agent orchestration, tool-use patterns, guardrails, and human-in-the-loop workflows. - Architect and operate AWS AI infrastructure (Bedrock, Bedrock Agents, Agent Core, SageMaker) alongside core AWS services (ECS/EKS, Lambda, S3, DynamoDB, RDS, API Gateway). - Design and implement scalable microservices and distributed systems in Java, TypeScript, and Python that power the Archer AI platform. - Build CI/CD pipelines for AI workloads — including LLM evaluation pipelines and automated regression testing for AI outputs — using Terraform, CloudFormation, Docker, Kubernetes, and GitHub Actions. - Drive AI-specific operational practices: observability, drift detection, quality scoring, feedback loops, and incident response for non-deterministic systems. - Communicate technical concepts clearly to both technical and non-technical stakeholders; author AI specs, design documents, and architectural decision records. - Mentor engineers, conduct thorough code reviews, and champion engineering excellence. Qualifications - Deep expertise in the AI software development lifecycle with a specification-first mindset. - Experience authoring AI feature specs (acceptance criteria, evaluation metrics, prompt contracts). - Track record of shipping AI-powered features through multiple product cycles with engineering rigor. - Strong hands-on experience with Amazon Bedrock, Bedrock Agents, Agent Core, SageMaker, and Amazon Q. - Solid knowledge of core AWS infrastructure including compute (ECS/EKS, Lambda), databases (RDS, DynamoDB, ElastiCache), networking (VPC, ALB, CloudFront), and security (IAM, KMS, Secrets Manager). - Experience architecting AI infrastructure pipelines with cost optimization and high availability. - Hands-on experience building production applications with Spring AI. - Solid understanding of LLM application patterns (prompt management, RAG, context orchestration, vector stores, evaluation) and agentic workflows (multi-step agents, tool-use orchestration, planning loops). - 5+ years of professional software engineering with strong proficiency across Java (Spring Boot, Spring Cloud), TypeScript (Node.js, modern frameworks), and Python (AI tooling, evaluation frameworks). - Experience designing and operating distributed systems at scale. - Familiarity with event-driven architectures, message brokers (Kafka, SQS/SNS), caching (Redis, ElastiCache), and relational/NoSQL database design. - Proficiency in CI/CD pipelines, Infrastructure as Code (Terraform, CloudFormation), containerization (Docker, Kubernetes/EKS), and GitOps workflows. - Excellent analytical skills and the ability to tackle complex, ambiguous challenges independently. - Outstanding written and verbal communication — able to articulate technical concepts to diverse audiences and collaborate effectively across teams. - Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field (or equivalent practical experience). Benefits - At Infios, we're not just looking for employees; we're looking for partners in innovation, growth, and purpose. - We meet you on your journey, equipping you with the tools and opportunities to build the future you envision. - We are committed to creating a safe and welcoming environment where every individual’s unique experiences and perspectives are valued.

Role Description We are looking for an Engineer to add substantial value to Cityblock’s technology platform used by our various engineering and product teams. You will join our Platform Engineering team whose goal is to make developing and deploying code at Cityblock more efficient, reliable, secure, and generally…pleasant! Our existing applications generally use: - Typescript - Node.js - GraphQL - TypeGraphQL - React - PostgreSQL We leverage GCP through: - Cloud Run - BigQuery - GCS - Cloud Functions On the Platform Team, we also work heavily with tools like: - Terraform - Datadog - Github Actions - Tonic - Apollo Responsibilities: - Design, build, and maintain cloud infrastructure on GCP using Terraform, with an emphasis on reusable modules, clear ownership boundaries, and safe change management. - Own and evolve our CI/CD pipelines, developer environments, and deployment tooling to keep our software and data engineers productive. - Execute infosec initiatives: vulnerability management, access controls, secrets management, audit logging, compliance evidence collection (HIPAA, SOC 2), and incident response. - Build observability into our systems—metrics, logs, traces, alerting, and SLOs—so we can detect and resolve issues before they impact Members or care teams. - Partner with software and data engineers to unblock them on infrastructure, database, networking, and deployment challenges, and provide paved-road patterns that make the secure path the easy path. - Support our data platform, including infrastructure for dbt, data warehouses, orchestration, and pipelines that power clinical analytics and operations. - Leverage AI-assisted development tools (Cursor, Claude Code) to accelerate Terraform development, automate toil, write runbooks and documentation, and tackle complex migrations—while maintaining rigorous standards for correctness, security, and maintainability. - Drive cost visibility and optimization across our GCP footprint. - Write clean, well-tested infrastructure code and automation that will stand the test of time. - Participate in creating and maintaining strict compliance, data privacy, and security measures. - Help recruit highly capable engineers to the team from diverse backgrounds. - Mentor engineers and new team members—including sharing best practices for effective AI-assisted development and secure-by-default infrastructure patterns—while continuously upgrading your own skills. - Collaborate with clinical teams, product managers, and designers when platform decisions affect end-user experience. Qualifications - You have 6+ years of experience in platform, infrastructure, DevOps, SRE, or a closely related engineering role. - At least 2+ years of experience leading technical initiatives or members of an engineering team. - You are invigorated by the complexities of building reliable, secure infrastructure for health tech. - You have a process-oriented mindset and are comfortable writing and debating design documents, RFCs, and postmortems. - Deep experience with Terraform (or a comparable IaC tool) in a production environment, including module design, state management, and safe rollout practices. - Strong working knowledge of a major cloud provider (GCP preferred; AWS or Azure acceptable with willingness to learn GCP). - Hands-on experience executing security and compliance work—IAM, secrets management, vulnerability remediation, audit preparation, or similar. - Experience building and operating CI/CD pipelines and developer tooling. - You have hands-on experience using AI coding assistants (such as Cursor, Claude Code, Copilot, or similar) as part of your daily workflow, and have developed good judgment about when to rely on them and when not to. - You have a passion for doing mission-oriented work. - You enjoy working with a diverse group of people with different expertise. 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 Range The expected salary range for this position is: $139,000.00 - $183,000.00 Annual. Company Description 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. We do not accept unsolicited resumes from outside recruiters/placement agencies. Cityblock will not pay fees associated with resumes presented through unsolicited means.

Role Description The AI Software Engineer supports and scales adoption of the enterprise AI platform by troubleshooting AI behavior, identifying systemic gaps, and driving continuous improvement in platform performance and usage. This role works directly with internal associates to resolve issues and partners closely with engineering teams to diagnose root causes across LLMs, agent workflows, tools (MCP), and backend systems. Positioned at the intersection of technical support, product enablement, and AI system operations, this role goes beyond traditional support to actively improve how the platform operates and is used. As part of our Software Engineer hiring efforts, we're using a video screening process and coding assessment. To learn more and to help prepare for this, click here! Qualifications - Up to 3 years’ experience in a technical support, QA, SDET, or engineering-adjacent role (including internships, co-ops, or academic projects) - Bachelor’s degree in Computer Science, Computer Information Systems, Business Information Systems, or a related technical field - Demonstrated ability to troubleshoot and debug technical issues, focusing on root cause analysis - Foundational experience or exposure to: - API testing (Postman or similar) - Reading logs and debugging application behavior - Basic SQL or data inspection - Exposure to or strong interest in AI/LLM-based systems (prompting, chatbots, RAG, or agents) through coursework, projects, or hands-on experimentation - Experience using or willingness to learn AI-powered development tools (e.g., Cursor, Claude Code) - Strong communication skills with the ability to translate technical issues into clear explanations for non-technical users - Demonstrated curiosity and ability to learn quickly in a fast-evolving technical environment Requirements - Qualified candidates must complete a video interview assessment after applying as the next step, to be completed within 7 days of receiving the link. - Set aside 40-45 minutes for the self-guided assessment that includes games and questions. - Find a quiet place to record and be camera-ready. - You’ll need a smartphone, tablet, or desktop computer with your camera and microphone enabled. - You’ll answer questions to share your skills and experience and bring your personality to the interview. - This step accelerates the interview process, moving qualified candidates to hiring manager interview fast. - Experience supporting or building AI/agent-based applications is preferred. - Familiarity with the following is preferred: - Retrieval-Augmented Generation (RAG) - Tool/agent orchestration - Prompt engineering Benefits - The national average salary range for this role is $65-85k in base pay, exclusive of any bonuses and benefits. - Actual salary offered will vary and may be above or below the range based on various factors including but not limited to location, experience, performance, and internal pay alignment. - We do not anticipate that candidates hired will begin at the top of the range; however, from time to time, it may occur on a case-by-case basis. - Other rewards and benefits may include: - 401(k) match - Medical, Dental, Vision - Paid-Time-Off - For more information, please visit careers.ascensus.com/#Benefits .