[Hiring] Applied ML Engineer @Bask Health

Role Description

We're looking for an Applied ML Engineer, Agents & Automation to design, build, and deploy intelligent systems that automate complex workflows across Bask Health's telehealth platform.

• Bask Health brings together merchant operations, patient experiences, clinical workflows, pharmacy coordination, and commerce tools.
• You'll help build AI-powered systems that can coordinate these steps while operating within clearly defined permissions and reliability requirements.
• This role focuses on developing production AI agents that use large language models, application tools, retrieval systems, and workflow orchestration to complete approved tasks.
• You'll work on the technical infrastructure that allows agents to retrieve information, select appropriate tools, execute actions, handle failures, and maintain context throughout multi-step processes.
• Combine applied machine learning with strong software engineering practices.
• Your work may support merchant operations, internal administrative processes, patient-related coordination, and pharmacy workflows.
• Collaborate with product managers, backend engineers, applied AI engineers, and operational stakeholders to identify opportunities where automation can reduce manual work and improve consistency.
• Ensure that automated systems operate within approved business and clinical boundaries and do not independently perform actions that require licensed professional judgment.
• This is a hands-on engineering position with meaningful ownership over agent behavior, automation architecture, and production reliability.
• Build reusable systems, measure their performance, and improve them based on real-world results.
• Understand both the potential and limitations of AI agents and enjoy building systems that are useful, measurable, secure, and dependable.

Qualifications

• 3+ years of professional experience in software engineering, machine learning engineering, or a closely related technical field.
• Experience building and deploying production software applications.
• Strong programming skills in Python, TypeScript, or comparable languages.
• Hands-on experience developing AI-powered applications or intelligent automation systems.
• Familiarity with large language models and modern generative AI development techniques.
• Experience integrating model APIs into production software.
• Understanding of tool calling, function calling, and AI application orchestration.
• Experience building backend services and application APIs.
• Familiarity with asynchronous programming and distributed application workflows.
• Understanding of workflow state management and multi-step process execution.
• Experience integrating internal services, databases, and third-party APIs.
• Familiarity with structured model outputs and schema validation.
• Understanding of prompt engineering and model behavior evaluation.
• Ability to identify and troubleshoot unreliable AI-generated outputs.
• Experience designing automated tests for production software.
• Familiarity with logging, monitoring, and production troubleshooting.
• Understanding of authentication, authorization, and secure API design.
• Ability to implement error handling, retries, and recovery mechanisms.
• Familiarity with cloud-based application deployment.
• Understanding of data pipelines and structured application data.
• Ability to evaluate technical tradeoffs between AI-driven automation and deterministic software.
• Experience working with Git, code review, and collaborative engineering practices.
• Ability to translate operational requirements into reliable technical solutions.
• Strong analytical thinking and problem-solving skills.
• Ability to independently own engineering projects and communicate effectively with cross-functional teams.

Requirements

• Design, build, and deploy AI agents that automate approved workflows across Bask Health's platform.
• Develop agent architectures that combine large language models, tools, APIs, and application logic.
• Build multi-step automation systems that coordinate tasks across multiple services.
• Implement reliable tool-calling and function-execution capabilities.
• Develop agent orchestration logic for task planning, execution, and completion.
• Build reusable components for agent state management, context handling, and workflow execution.
• Integrate AI agents with internal APIs, databases, and approved external services.
• Develop retrieval capabilities that provide agents with relevant information and application context.
• Design structured outputs and validation systems for agent-generated actions.
• Implement permission checks and authorization controls for automated tool execution.
• Build human approval and confirmation steps for sensitive or consequential actions.
• Develop safeguards against prompt injection, unauthorized actions, and unreliable model behavior.
• Implement retry logic, error recovery, timeouts, and fallback mechanisms.
• Build monitoring and tracing systems that make agent behavior observable and debuggable.
• Create automated tests for tool selection, workflow execution, and task completion.
• Develop evaluation datasets and benchmarks for agent accuracy and reliability.
• Measure agent success rates, task completion, latency, and operational costs.
• Investigate agent failures and improve prompts, tools, models, and orchestration logic.
• Evaluate whether model adaptation, fine-tuning, or alternative ML approaches improve task performance.
• Collaborate with product teams to identify repetitive workflows suitable for automation.
• Develop AI-powered automation for merchant configuration and operational tasks.
• Support approved administrative workflows involving patient and pharmacy coordination.
• Work with backend engineers to integrate agent systems into production infrastructure.
• Design event-driven automation triggered by approved application events.
• Optimize agent performance, infrastructure usage, and model inference costs.
• Build internal tools that help engineers inspect, test, and troubleshoot agent workflows.
• Participate in architecture discussions, code reviews, and engineering planning.
• Own assigned automation initiatives from technical design through deployment and continuous improvement.

Benefits

• Experience building production AI agents or agent-based automation systems.
• Familiarity with LangGraph, LangChain, Semantic Kernel, or comparable agent orchestration frameworks.
• Experience with OpenAI, Anthropic, or similar model APIs.
• Experience implementing multi-agent workflows or coordinated agent execution.
• Familiarity with retrieval-augmented generation and vector search.
• Experience building AI applications with persistent state or long-running workflows.
• Experience with event-driven architectures and workflow engines.
• Familiarity with AWS Lambda, SQS, EventBridge, or comparable cloud services.
• Experience with Temporal or similar durable workflow orchestration platforms.
• Experience with model fine-tuning, supervised learning, or task-specific model adaptation.
• Familiarity with machine learning evaluation methodologies and experiment tracking.
• Experience developing benchmarks for agent task completion and tool-use accuracy.
• Experience with agent observability and tracing tools.
• Familiarity with human-in-the-loop approval systems.
• Experience implementing sandboxed tool execution or restricted automation environments.
• Understanding of prompt injection risks and agent security practices.
• Experience building automation for SaaS platforms or e-commerce operations.
• Familiarity with healthcare, telehealth, or pharmacy-related workflows.
• Understanding of HIPAA and healthcare data privacy considerations.
• Experience using AI-assisted development tools such as Cursor or Claude Code.