• Responsible for architecting solutions achieving customer business outcomes • Develop and articulate compelling, accurate, and relevant proposals • Provide technical expertise to sales teams and customers • Develop customer proposals and critically review them • Quantify the impact of business problems and position business value • Communicate how the solution value propositions address customer business needs • Drive the Account Business Planning process leveraging knowledge of industry trends and customer’s technical environment

• Build automated vendor intelligence pipelines that continuously collect and parse AI system cards, model benchmarks (MMLU, HumanEval, etc.), security disclosures, and public vendor documentation • Design synthesis systems that map disparate vendor information to our risk taxonomy—translating technical capabilities into governance-relevant risk signals • Implement quality evaluation for generated risk profiles, ensuring accuracy and detecting when vendor information conflicts or becomes stale • Create adaptive interpretation systems that adjust risk assessments based on organizational context and risk appetite • Research and prototype novel approaches to multi-source information synthesis and cross-vendor comparison

Role Description We are looking for a Staff Engineer to add substantial value to Cityblock’s technology platform used by our care providers and Members. Our work is centered on supporting outreach to patients, capturing data on their medical, behavioral, and social needs, and then integrating that with homegrown and external applications to enable personalized care for our members. You will join our Engineering team which works closely with our design, product management, data science, and clinical operations teams to create a digital product experience tailored to our Member’s needs. Our existing applications generally use: - Typescript - Node.js - PostgreSQL - dbt for our data transformation layer - Google Cloud Platform (GCP) In addition to leveraging React and GraphQL for internal applications, our engineers integrate third party platforms and data sources via FHIR to provide a seamless experience for our care teams and clinical providers. We embrace AI-assisted software development as a core part of how we build. Our engineers use tools like Cursor and Claude Code daily to accelerate development, write higher-quality code, refactor complex systems, and ship features faster. We’re looking for engineers who are excited to work alongside AI tooling—thoughtfully directing these tools, reviewing their output critically, and using them to multiply their impact across the stack. We are looking for someone with experience working across the full stack and comfort with querying and analyzing data to drive decisions. If you want to solve complex problems, grow a talented pool of engineers, and are an amazing teammate, we want to hear from you! Qualifications - You have 6+ years experience writing production code. - At least 2+ years experience leading members of an engineering team. - You are invigorated by the complexities of building great health tech. - You have a process-oriented mindset, and are comfortable writing and debating around design documents. - You enjoy working across the stack and building features end-to-end. - 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. Requirements - Design, build, and implement population health management tools and cloud infrastructure. - Leverage AI-assisted development tools (Cursor, Claude Code) to accelerate feature delivery, improve code quality, and tackle complex refactors—while maintaining rigorous standards for correctness and maintainability. - Build and maintain data models in dbt to power analytics, reporting, and downstream applications that inform clinical care. - Integrate third party platforms via API and surface data to our users. - Query and analyze data to inform architectural decisions and system design. - Write and review code up and down the stack as needed, including reviewing AI-generated code with a critical eye. - Ensure we are using industry best practices for producing reliable software that works beautifully. - Write clean, well-tested code 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 apply technical expertise to help others grow, while continuously upgrading your own skills and thinking as an engineer. - Collaborate with our clinical teams, product managers, and designers to build features that are highly efficient to support field-based operations and engage patients. Benefits - Health insurance - Life insurance - Retirement benefits - Participation in the company’s equity program - Paid time off, including vacation and sick leave The expected salary range for this position is: $145,000.00 - $210,000.00 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 Engineer is part of a highly collaborative team that develops cutting-edge machine learning (ML) and artificial intelligence (AI) models to solve complex business challenges and improve member health outcomes. In this role, you will work on high-impact projects involving advanced ML techniques, including large language models (LLMs) and generative AI. You’ll have the opportunity to experiment with state-of-the-art algorithms, push the boundaries of AI capabilities, and contribute to innovative solutions that drive real-world value. Qualifications - Bachelor's degree required; in lieu of a degree, six (6) years of relevant experience required. - Prior professional, co-op, or internship experience developing AI/ML solutions, or relevant coursework. - Basic understanding of fundamental ML concepts, algorithms, and statistical techniques. - Basic experience working with databases, SQL, and data manipulation. - Strong problem-solving skills and a willingness to learn. - Hands-on professional experience developing ML models for real-world applications. - Intermediate proficiency with cloud-based ML platforms (e.g., Databricks, AWS SageMaker, or Azure ML). - Intermediate knowledge of model performance monitoring and optimization techniques. - Experience working with large-scale data pipelines and distributed computing frameworks (e.g., Spark). - Familiarity with CI/CD and ML Ops/LLM Ops principles to collaborate effectively with deployment teams. - Experience working with large language models (LLMs) and generative AI technologies. - Ability to present clear and concise technical concepts to both technical and non-technical stakeholders. - Significant professional experience and knowledge in AI/ML engineering with a track record of developing models at scale. - Advanced proficiency in AI/ML model architecture, optimization, and explainability techniques. - Advanced experience integrating AI solutions with business applications and APIs. - Extensive experience working with large language models (LLMs) and generative AI in production environments. - Advanced understanding of AI model lifecycle management, governance, and operationalization. - Leadership experience in mentoring and guiding AI engineering best practices. - Strong ability to engage with executives and business leaders to drive AI strategy. Requirements - Develops Artificial Intelligence and Machine Learning solutions to solve business problems and improve member health outcomes, incorporating (but not limited to): - Large language models (LLMs) and generative AI applications - Machine learning models - Natural language processing (NLP) - Optimization and mathematical programming - Recommendation systems - Builds and refines data pipelines for feature engineering and ML model input, ensuring efficient and scalable data handling. - Collaborates with data engineering teams to acquire, clean, and prepare data for model training. - Supports model evaluation, testing, and performance monitoring in pre-production environments. - Works within cloud-based ML platforms (e.g., Databricks) to develop and optimize AI models. - Understands ML Operations principles and collaborates with CI/CD and ML Operations engineers for model deployment and monitoring. - Participates in peer code reviews and follows best practices for software development in AI. - Stays up to date with industry trends and new developments in AI/ML. - Develops and refines prompt engineering techniques for optimizing interactions with LLMs and generative AI applications. - Consistently demonstrates high standards of integrity by supporting the Lifetime Healthcare Companies’ mission and values, adhering to the Corporate Code of Conduct, and leading to the Lifetime Way values and beliefs. - Maintains high regard for member privacy in accordance with the corporate privacy policies and procedures. - Regular and reliable attendance is expected and required. - Performs other functions as assigned by management. - Contributes to the AI/ML model lifecycle, ensuring reproducibility, scalability, and maintainability of solutions. - Works with stakeholders to translate business objectives into AI/ML formulations and measurable success criteria. - Optimizes and fine-tunes ML models for performance, explainability, and efficiency. - Develops solutions using large language models (LLMs) and generative AI frameworks. - Supports the integration of AI models with enterprise applications, APIs, or data pipelines. - Engages in continuous learning and shares knowledge on new ML techniques and best practices. - Enhances team efficiency through the adoption of automation tools for model training, evaluation, and monitoring. - Leads the discovery and solutioning process, working with company stakeholders to identify high-impact AI opportunities. - Designs and implements scalable AI architectures that integrate with enterprise systems and support business operations. - Leads initiatives related to large language models (LLMs) and generative AI, ensuring alignment with business needs. - Mentors junior team members and fosters a culture of engineering excellence. - Collaborates with Operations and CI/CD teams to improve AI model deployment pipelines and monitoring strategies. - Recommends and influences best practices for AI model governance, versioning, and compliance. - Engages with leadership and cross-functional teams to align AI strategies with business goals. Benefits - Participation in group health and/or dental insurance - Retirement plan - Wellness program - Paid time away from work - Paid holidays Compensation Range(s) - Level I Min - 65,346 Max - 117,622 - Level II Min - 79,068 Max - 142,322