Applied ML Engineer - Agents & Automation

Applied ML Engineer, Agents & Automation

Bask Health · United States (Remote) · Full-time · Posted 2026-11-12

Workplace: remote

Department: AI & Machine Learning

Description

About the Role

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. Many of these processes involve multiple applications, structured information, business rules, and repetitive tasks. 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.

You'll combine applied machine learning with strong software engineering practices. Depending on the use case, this may involve model selection, fine-tuning, task-specific evaluation, or other machine learning techniques that improve agent performance. You'll also recognize when deterministic software and conventional automation are more reliable than model-driven decisions.

Your work may support merchant operations, internal administrative processes, patient-related coordination, and pharmacy workflows. You'll collaborate with product managers, backend engineers, applied AI engineers, and operational stakeholders to identify opportunities where automation can reduce manual work and improve consistency.

Because Bask operates in healthcare-related environments, agents must be designed with appropriate safeguards, access controls, auditability, and human approval requirements. You'll help 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. You'll build reusable systems, measure their performance, and improve them based on real-world results.

We're looking for someone who understands both the potential and limitations of AI agents and enjoys building systems that are useful, measurable, secure, and dependable.

What You'll Do

• 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.

Requirements

• 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.

Nice to Have

• 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.

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