Software Engineer, AI Platform

Job not on LinkedIn

🔥 11 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 25%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Just posted.
• Jobs at this company usually fill in 60 days.
• 102 open roles for a team of 16.
• No salary listed.

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Bask Health

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

💰 Pre Seed Round on 2022-05

Healthcare • Consulting • Logistics

Bask Health is a robust platform providing a comprehensive suite of customizable telehealth solutions. It offers tools such as a questionnaire builder, patient portals, and pharmacy fulfillment services, all secured with strong encryption and HIPAA-compliance. Bask Health seamlessly integrates telehealth and e-commerce, enabling streamlined patient care from consultation to delivery. The platform supports entrepreneurs, doctors, and developers by offering scalable no-code solutions that enhance user experience and business growth. With its nationwide pharmacy network, Bask Health empowers businesses to efficiently manage prescriptions, patient data, and order fulfillment across the entire digital health landscape.

📋 Description

• Design, build, and maintain shared infrastructure for AI-powered applications across Bask Health • Develop backend services and APIs supporting model integration and AI application execution • Build reusable components for consistent large language model access • Develop centralized model integration services and inference request handling • Implement routing and configuration for multiple model providers • Manage 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 prompt configuration, versioning, and controlled update infrastructure • Create shared services for embeddings, retrieval, and knowledge-grounded AI applications • Build APIs and integration patterns supporting AI agents and workflow automation • Develop secure data access components for AI applications • Ensure tenant boundaries and application authorization requirements are respected • Build observability 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, service availability, backend performance, throughput, and infrastructure costs • Design scalable asynchronous processing and background job systems • Integrate AI platform services with application databases and backend infrastructure • Build internal developer tools and documentation simplifying AI application development • Collaborate with applied AI engineers and support machine learning engineers with model-serving and evaluation integrations • Investigate production incidents and resolve infrastructure-related failures • Participate in architecture discussions, technical planning, and code reviews • Establish reusable patterns for secure and maintainable AI integrations • Own platform services from technical design through deployment, monitoring, and continuous improvement

🎯 Requirements

• 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 • Nice to Have: Experience building infrastructure for AI or machine learning applications • Nice to Have: Familiarity with OpenAI, Anthropic, or comparable model APIs • Nice to Have: Experience building model gateways, inference proxies, or centralized AI integration services • Nice to Have: Familiarity with multi-model routing and provider fallback strategies • Nice to Have: Experience with TypeScript and Node.js backend development • Nice to Have: Familiarity with tRPC, Prisma, Drizzle, or similar application development tools • Nice to Have: Experience working with AWS Lambda, SQS, EventBridge, or comparable cloud services • Nice to Have: Familiarity with serverless infrastructure and infrastructure-as-code tools • Nice to Have: Experience with SST or similar application deployment frameworks • Nice to Have: Familiarity with containerization and distributed service deployment • Nice to Have: Experience building systems for API rate limiting, usage metering, or cost allocation • Nice to Have: Familiarity with embeddings, vector databases, and retrieval infrastructure • Nice to Have: Experience supporting retrieval-augmented generation applications • Nice to Have: Experience building shared infrastructure for AI agents or automated workflows • Nice to Have: Familiarity with prompt management, versioning, and configuration systems • Nice to Have: Experience implementing AI request tracing and model observability • Nice to Have: Experience developing internal SDKs, libraries, or developer platforms • Nice to Have: Understanding of multi-tenant SaaS architecture and data isolation • Nice to Have: Familiarity with HIPAA and healthcare data privacy considerations • Nice to Have: Experience using AI-assisted development tools such as Cursor or Claude Code

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