hc1 RxView™
We are seeking a results-oriented Director of Engineering to lead our engineering organization through a period of accelerated innovation, automation, and growth. This role will be instrumental in delivering hc1’s next generation of high-quality, AI-enabled products by streamlining development workflows, embedding automation (including QA automation) into our SDLC, and ensuring that engineering excellence drives business outcomes.
Ready to make your application Please do read through the description at least once before clicking on Apply. What you’ll do: Lead and Scale the Engineering Team: Build, mentor, and inspire a high-performing team of architects, engineers, and QA professionals to meet hc1’s technology and business goals Drive Automation and AI Adoption: Identify opportunities to streamline manual tasks across the SDLC (e.g., QA, deployment, monitoring) Champion the use of AI tools for code review, defect detection, test case generation, and performance monitoring Deliver High-Quality Products: Ensure all software releases meet rigorous quality standards, with a focus on scalability, reliability, and user experience Collaborate with Product Management to translate requirements into elegant, functional software solutions Translate AI ideas into production-ready software solutions Enhance Engineering Processes: Implement agile best practices, CI/CD pipelines, and test-driven development frameworks to improve throughput Optimize workflows for cross-functional collaboration between engineering, product, and client success teams Align Technology with Business Outcomes: Partner with stakeholders to ensure that engineering priorities align with company OKRs, growth objectives, and customer value creation Contribute to technical roadmaps and architectural decisions that enable future scalability Foster a Culture of Innovation: Encourage experimentation with emerging tools, frameworks, and methodologies Promote knowledge-sharing and continuous learning within the team Own Departmental Performance: Monitor engineering KPIs (velocity, quality, automation coverage, satisfaction metrics) to identify areas of improvement Complete other duties as assigned Requirements
What you bring: Experience: 8+ years of progressive software engineering experience, with 5+ years leading teams in a SaaS, cloud-native environment Proven Expertise in Automation: Hands-on experience implementing automated testing frameworks, CI/CD pipelines, and DevOps practices. Exposure to AI-driven QA or development tools is a strong plus Technical Leadership: Experience with delivering customer facing AI/ML solutions. Deep understanding of modern architectures (microservices, event-driven systems) and ability to guide solution design decisions Commitment to Quality: Track record of delivering robust, scalable, and secure products on time and on budget Business Acumen: Ability to align technology initiatives with business strategy and communicate value to executive stakeholders Collaboration Skills: Adept at cross-functional leadership, working with Product, Marketing, and Customer Success teams to drive results Mindset: Curious, data-driven, and willing to roll up sleeves to solve complex challenges AI technology: AWS Bedrock, Sagemaker, LLM Container technologies: Docker, ECS Cloud infrastructure: AWS (EC2, SQS, S3, Lambda) Tooling: Github, Jenkins, TravisCI, Artifactory, JIRA
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Ready to make your application Please do read through the description at least once before clicking on Apply. What you’ll do: Lead and Scale the Engineering Team: Build, mentor, and inspire a high-performing team of architects, engineers, and QA professionals to meet hc1’s technology and business goals Drive Automation and AI Adoption: Identify opportunities to streamline manual tasks across the SDLC (e.g., QA, deployment, monitoring) Champion the use of AI tools for code review, defect detection, test case generation, and performance monitoring Deliver High-Quality Products: Ensure all software releases meet rigorous quality standards, with a focus on scalability, reliability, and user experience Collaborate with Product Management to translate requirements into elegant, functional software solutions Translate AI ideas into production-ready software solutions Enhance Engineering Processes: Implement agile best practices, CI/CD pipelines, and test-driven development frameworks to improve throughput Optimize workflows for cross-functional collaboration between engineering, product, and client success teams Align Technology with Business Outcomes: Partner with stakeholders to ensure that engineering priorities align with company OKRs, growth objectives, and customer value creation Contribute to technical roadmaps and architectural decisions that enable future scalability Foster a Culture of Innovation: Encourage experimentation with emerging tools, frameworks, and methodologies Promote knowledge-sharing and continuous learning within the team Own Departmental Performance: Monitor engineering KPIs (velocity, quality, automation coverage, satisfaction metrics) to identify areas of improvement Complete other duties as assigned Requirements
What you bring: Experience: 8+ years of progressive software engineering experience, with 5+ years leading teams in a SaaS, cloud-native environment Proven Expertise in Automation: Hands-on experience implementing automated testing frameworks, CI/CD pipelines, and DevOps practices. Exposure to AI-driven QA or development tools is a strong plus Technical Leadership: Experience with delivering customer facing AI/ML solutions. Deep understanding of modern architectures (microservices, event-driven systems) and ability to guide solution design decisions Commitment to Quality: Track record of delivering robust, scalable, and secure products on time and on budget Business Acumen: Ability to align technology initiatives with business strategy and communicate value to executive stakeholders Collaboration Skills: Adept at cross-functional leadership, working with Product, Marketing, and Customer Success teams to drive results Mindset: Curious, data-driven, and willing to roll up sleeves to solve complex challenges AI technology: AWS Bedrock, Sagemaker, LLM Container technologies: Docker, ECS Cloud infrastructure: AWS (EC2, SQS, S3, Lambda) Tooling: Github, Jenkins, TravisCI, Artifactory, JIRA
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