Head Of Engineering - Digital Health & Ai

Who are we?MiMIAT Health has developed apatient-controlled longitudinal health recordthat makesdisease evolution visibleand enablesdata continuity across fragmented care settingsfor multidisciplinary teams managinghard-to-diagnose diseases .Our work has been recognised throughPRECISEU Best Practice Recognition, AstraZeneca ACCIÓN, Google for Startups for Sustainable Development and NVIDIA Inception .We are also part ofCOST Action CA*** , focused on blood, tissues and cells as starting materials for advanced therapies.MiMIAT is now developingMimi, a multilingual voice AI layer built on top of its patient-controlled longitudinal health record .Rather than functioning as a symptom tracker or standalone chatbot, Mimi is intended to continuously reconstruct and interpret each patient’s disease trajectory across clinical records, biomarkers, medication history, treatment response, patient-reported data, connected devices and family history.Mimi will identifymissing context, contradictions and changes that the current diagnosis or treatment may no longer explain , transforming fragmented information into structured, reviewable clinical intelligence for patients and multidisciplinary care teams.What are we looking for?We’re looking for an experiencedHead of Engineeringto lead MiMIAT’s technical evolution during its next stage of product development.You will work directly with theFounder & CEO and MiMIAT’s current technical contributors , taking ownership of the assessment of the existing platform, the definition of technical priorities and the architecture required for MiMIAT’s clinical-data and AI roadmap.The role combineshands-on engineering leadership, system architecture and technical execution.You should be capable of strengthening an existing production environment while defining the foundations required for clinical-record processing, longitudinal patient intelligence and Mimi.We are specifically looking for someone who has alreadybuilt and operated healthcare technology in production , understands the responsibilities involved in handling sensitive health data, and has practical experience translating AI capabilities into reliable products.The collaboration will begin at approximately8 to 12 hours per week , managed flexibly around the person’s existing professional commitments.What will you do?Review MiMIAT’s current architectureacross the patient application, clinician platform, backend services, databases, cloud infrastructure and external integrations.Identify the most important technical risks, dependencies and scalability limitationsaffecting the current product.Define a prioritised engineering roadmapcovering platform stability, security, maintainability and future product development.Lead architectural decisionsacross backend services, APIs, databases, authentication, permissions and sensitive health-data flows.Define the technical foundations required for clinical-record ingestion, document processing, structured information extraction and longitudinal patient context.Design the initial architecture for Mimi , including multilingual voice interaction, contextual retrieval, structured outputs, model evaluation and human review.Assess and select appropriate AI models, APIs, infrastructure and external services , determining what MiMIAT should build internally and what should be integrated.Establish practical engineering standardsacross code review, testing, deployment, monitoring, documentation and access management.Provide hands-on technical direction and code-review supportto MiMIAT’s engineering contributors.Work with clinical, behavioural-science, regulatory and privacy contributors totranslate multidisciplinary requirements into executable technical decisions.Help identify future requirements acrossengineering, AI, data, infrastructure and cybersecurity.Who are you?You haveat least 7 years of professional software-engineering experience , including substantial responsibility for backend systems, cloud infrastructure and production architecture.You haveat least 3 years of direct experience in digital health, HealthTech, MedTech, clinical software or another regulated healthcare environment.You have personallybuilt, shipped or materially led at least one healthcare product operating in a live production environmentand used by patients, clinicians, researchers or healthcare organisations.You haveat least 2 years of experience in technical leadership, system architecture or engineering ownership , with responsibility for making and defending system-level decisions.You haveat least 1 year of practical experience designing, integrating or operating AI-enabled software in production , ideally involving LLMs, retrieval systems, clinical-document processing, structured information extraction, conversational AI or voice technologies.You remaintechnically hands-onand are comfortable reviewing code, examining infrastructure, diagnosing failures and contributing directly where required.You have strong experience building and maintainingbackend services, APIs, databases, authentication, authorisation and secure data-access systems.You have professional experience withTypeScript or JavaScript and Node.js , or extensive experience in a closely comparable backend stack.You haveat least 3 years of experience operating cloud-based production systems , using AWS or another major cloud platform across deployment, access controls, monitoring and reliability.You understand the engineering requirements involved in handlingsensitive healthcare data , including privacy-by-design, permissions, traceability, data integrity and secure processing.You have led, mentored or provided technical direction to engineers and can establish clear standards acrosscode review, testing, deployment and documentation.You can make pragmatic decisions in an early-stage environment, distinguishingcritical technical risks from debt that can responsibly be deferred.You communicate architectural decisions, risks and trade-offs clearly acrossengineering, clinical, product, regulatory and non-technical stakeholders.You can sustain approximately8 to 12 hours per week during the initial phase , with proactive communication around progress, availability and blockers.Bonus pointsif you have experience withAI-enabled clinical products, multilingual voice systems, clinical-document intelligence, React Native, Expo, Next.js, MongoDB, FHIR, HL7, SaMD, EU MDR, ISO *** or ISO **.Benefits You will work directly with theFounder & CEOand have meaningful influence over MiMIAT’s technical architecture, engineering roadmap and AI direction.You will contribute tolive patient and clinician-facing products , rather than an idea-stage project or isolated prototype.You will help shapeMimi from its earliest technical stage , including the data, voice, AI and evaluation infrastructure required for its development.You will work alongside contributors acrossengineering, clinical care, behavioural science, regulatory affairs and health data privacy.You will join a mission-driven HealthTech company recognised throughPRECISEU, AstraZeneca ACCIÓN, Google for Startups for Sustainable Development and NVIDIA Inception.Current phase:The collaboration will begin on anunpaid/pro-bono basis at approximately 8 to 12 hours per week , with a formal mutual-fit review after the first six weeks.During this phase, both sides will work againstclearly agreed technical priorities, deliverables and milestonesto assess technical capability, consistency, communication, leadership and fit with MiMIAT’s team and current stage.Potential evolution:Where there isstrong mutual fit, demonstrated capability and consistent delivery against agreed milestones , the role may progressively expand inscope, weekly commitment and executive responsibility .Subject to MiMIAT reaching definedproduct, commercial and financing milestones , this could include a transition towards apaid part-time or full-time Head of Engineering role , together with a potential longer-term executive or equity structure.Any expanded arrangement would be negotiated and documented separately in writing before it begins.How to apply At this stage we are removing application instructions per formatting rules.We invite you to review the requirements and consider whether you meet the qualifications described above.#J-**-Ljbffr

at least 7 years of professional software-engineering experience , including substantial responsibility for backend systems, cloud infrastructure and production architecture. You have at least 3 years of direct experience in digital health, HealthTech, MedTech, clinical software or another regulated healthcare environment. You have personally built, shipped or materially led at least one healthcare product operating in a live production environment and used by patients, clinicians, researchers or healthcare organisations. You have at least 2 years of experience in technical leadership, system architecture or engineering ownership , with responsibility for making and defending system-level decisions. You have at least 1 year of practical experience designing, integrating or operating AI-enabled software in production , ideally involving LLMs, retrieval systems, clinical-document processing, structured information extraction, conversational AI or voice technologies. You remain technically hands-on and are comfortable reviewing code, examining infrastructure, diagnosing failures and contributing directly where required. You have strong experience building and maintaining backend services, APIs, databases, authentication, authorisation and secure data-access systems. You have professional experience with TypeScript or JavaScript and Node.js , or extensive experience in a closely comparable backend stack. You have at least 3 years of experience operating cloud-based production systems , using AWS or another major cloud platform across deployment, access controls, monitoring and reliability. You understand the engineering requirements involved in handling sensitive healthcare data , including privacy-by-design, permissions, traceability, data integrity and secure processing. You have led, mentored or provided technical direction to engineers and can establish clear standards across code review, testing, deployment and documentation. You can make pragmatic decisions in an early-stage environment, distinguishing critical technical risks from debt that can responsibly be deferred. You communicate architectural decisions, risks and trade-offs clearly across engineering, clinical, product, regulatory and non-technical stakeholders.

MiMIAT Health has developed a patient-controlled longitudinal health record that makes disease evolution visible and enables data continuity across fragmented care settings for multidisciplinary teams managing hard-to-diagnose diseases . Our work has been recognised through PRECISEU Best Practice Recognition, AstraZeneca ACCIÓN, Google for Startups for Sustainable Development and NVIDIA Inception . We are also part of COST Action CA***** , focused on blood, tissues and cells as starting materials for advanced therapies. MiMIAT is now developing Mimi, a multilingual voice AI layer built on top of its patient-controlled longitudinal health record . Rather than functioning as a symptom tracker or standalone chatbot, Mimi is intended to continuously reconstruct and interpret each patient’s disease trajectory across clinical records, biomarkers, medication history, treatment response, patient-reported data, connected devices and family history. Mimi will identify