[Hiring] Software Engineer, AI Platform @Bask Health

Role Description

We're looking for a Software Engineer, AI Platform to build and maintain the foundational software infrastructure that supports AI-powered applications across Bask Health.

• Build reusable APIs, model integration services, inference gateways, data access components, and operational tools.
• Work with backend technologies, cloud infrastructure, databases, model providers, and distributed systems.
• Focus on centralized model access, request routing, usage tracking, authentication, rate limiting, prompt configuration, observability, and infrastructure.
• Collaborate with applied AI engineers, machine learning engineers, product engineers, and infrastructure specialists.
• Ensure AI infrastructure respects privacy requirements, tenant isolation, access controls, and approved data-handling practices.
• Design systems that allow teams to innovate without compromising security or reliability.
• Hands-on engineering role with ownership over production infrastructure and shared developer capabilities.
• Write code, improve system architecture, investigate operational issues, and help establish engineering patterns.

Qualifications

• 3+ years of professional software engineering experience, preferably in backend, platform, or infrastructure engineering.
• Demonstrated experience building and maintaining production backend services.
• Strong programming skills in TypeScript, JavaScript, Python, or comparable backend languages.
• Experience designing and developing APIs and service integrations.
• Strong understanding of backend application architecture and distributed systems fundamentals.
• Familiarity with large language models and modern AI application integration patterns.
• Experience integrating third-party APIs or external services into production applications.
• Understanding of authentication, authorization, and secure service communication.
• Experience working with relational databases and application data models.
• Familiarity with asynchronous processing, background jobs, and event-driven systems.
• Experience designing systems that handle errors, retries, timeouts, and service failures.
• Understanding of cloud infrastructure and production deployment practices.
• Familiarity with automated testing and continuous integration workflows.
• Experience working with logging, monitoring, and production observability tools.
• Understanding of system performance, latency, scalability, and reliability.
• Experience designing reusable software components and shared engineering services.
• Familiarity with API versioning, configuration management, and service maintenance.
• Understanding of data privacy and secure application development.
• Experience using Git, code review, and collaborative software development practices.
• Ability to troubleshoot complex backend and infrastructure issues.
• Experience writing maintainable, well-documented production code.
• Ability to evaluate engineering tradeoffs involving performance, complexity, and operational costs.
• Experience collaborating with engineers across multiple product or technical teams.
• Strong technical problem-solving and analytical skills.
• Ability to independently own engineering projects from design through deployment.

Requirements

• Design, build, and maintain shared infrastructure for AI-powered applications across Bask Health.
• Develop backend services and APIs that support model integration and AI application execution.
• Build reusable components that allow engineering teams to access large language models consistently.
• Develop centralized model integration services and inference request handling.
• Implement routing and configuration capabilities for multiple model providers.
• Build systems for managing model API credentials, authentication, and access permissions.
• Develop request validation, structured output handling, and standardized error responses.
• Implement rate limiting, retries, timeouts, and fallback mechanisms for model API requests.
• Build usage tracking and cost monitoring for AI services.
• Develop infrastructure that supports prompt configuration, versioning, and controlled updates.
• Create shared services for embeddings, retrieval, and knowledge-grounded AI applications.
• Build APIs and integration patterns that support AI agents and workflow automation.
• Develop secure data access components for AI applications.
• Ensure AI services respect tenant boundaries and application authorization requirements.
• Build observability systems for model requests, latency, errors, and operational performance.
• Implement structured logging and distributed tracing across AI services.
• Develop automated testing and deployment pipelines for AI platform components.
• Improve infrastructure reliability, fault tolerance, and service availability.
• Optimize backend performance, throughput, and infrastructure costs.
• Design scalable asynchronous processing and background job systems.
• Integrate AI platform services with existing application databases and backend infrastructure.
• Build internal developer tools and documentation that simplify AI application development.
• Collaborate with applied AI engineers to identify common infrastructure needs.
• Support machine learning engineers with reliable model-serving and evaluation integrations.
• Investigate production incidents and resolve infrastructure-related failures.
• Participate in architecture discussions, technical planning, and code reviews.
• Establish reusable engineering patterns for secure and maintainable AI integrations.
• Own assigned platform services from technical design through deployment, monitoring, and continuous improvement.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Flexible working hours and remote work options.
• Generous vacation and paid time off policies.
• Professional development opportunities and support for continuous learning.