AI Technical Product Architect
Apex Systems Inc
AI Technical Product Architect
Location: RemoteEmployment Type: Contract to Perm Role Overview The Technical Product Architect for Artificial Intelligence (AI) owns the technical strategy, execution approach, and delivery timeline for AI-enabled product solutions. This role functions as a Solutions Architect and Principal Engineer, responsible for ensuring AI solutions are technically feasible, scalable, and aligned with product outcomes. Operating within a product-centric model, this individual will partner with product managers, designers, and engineers to shape solutions that transform healthcare. Key Responsibilities
- Define and own the AI solution architecture across patient, clinical, and operational domains.
- Lead technical execution, including architecture decisions, delivery planning, and quality assurance.
- Provide technical leadership and mentorship to engineering teams.
- Ensure AI solutions adhere to responsible AI principles and regulatory standards.
- Drive the integration of AI/ML models into production systems using modern MLOps practices.
- Collaborate with product leadership to align technical investments with business priorities.
- Translate product discovery insights into technical feasibility analyses, estimates, and delivery plans.
- Stay current with emerging AI technologies and identify opportunities for innovation.
- Minimum of 2 years in a technical product architecture or solution architecture role within software, data, or AI engineering.
- Minimum of 4 years in a lead or senior engineering role, guiding teams in the development of software products.
- Demonstrated experience with end-to-end AI solution delivery, including LLMs, predictive models, RAG, and MLOps.
- Experience in healthcare or another highly regulated technology environment is required.
- Proficiency in Python/Pyspark and Java programming.
- Experience building user interfaces with HTML, CSS, and JavaScript frameworks such as React or Angular.
- Strong system design and architecture skills, with a focus on cloud-native, scalable, and production-grade solutions.
- Knowledge of and experience implementing knowledge graphs (such as Neo4j) in production solutions.
- Experience implementing GraphRAG to improve LLM response in production AI/ML products.
- Proficiency with public cloud platforms, ideally Azure.
- Expertise across APIs, microservices, systems integration, event-driven architectures, and data engineering.
- Experience designing production AI/ML applications using big data technologies and data pipeline orchestration tools.
Vacancy posted 19 hours ago
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