Senior AI/ML Engineer, Applications & Automation

This is a fully remote position, open to applicants in Illinois, +1 more state.

📋 Description

• Create machine learning models, agents, and automation workflows for managing terminology, producing content, mapping, and validation.

• Construct agentic workflows utilizing LLMs, tools, APIs, knowledge sources, retrieval capabilities, and structured business rules.

• Develop and oversee retrieval-augmented generation solutions, vector and semantic search functionalities, and strategies for prompt and context management.

• Collaborate with the data science team to integrate and operationalize existing agents, while contributing to the roadmap for model and agent development.

• Take responsibility for the deployment, monitoring, troubleshooting, and ongoing enhancement of AI workflows in a production environment.

• Conduct root-cause analysis and implement durable solutions for failures or unexpected outputs.

• Design evaluation, testing, and observability protocols for AI systems.

• Establish controls for auditability, explainability, and human-in-the-loop review within clinically sensitive workflows.

• Create cloud-based solutions utilizing AWS services such as Amazon Bedrock, SageMaker, and Lambda.

• Employ CI/CD, containerization, automated testing, and secure development methodologies.

• Work alongside clinical, mapping, product, data science, and engineering teams to translate workflows into actionable solutions.

• Assess where AI automation is suitable, where deterministic logic is necessary, and where human review must be retained.

⛳️ Requirements

• Over 5 years of experience in AI/ML engineering, data science, machine learning engineering, or related fields, with a solid foundation in applied machine learning.

• Practical experience in building agents and agentic workflows, including orchestration and tool or function invocation.

• Direct experience in constructing RAG solutions, encompassing embeddings, vector databases, semantic search, and context engineering.

• Hands-on MLOps experience in deploying models and agents to production, including deployment, versioning, monitoring, and CI/CD across diverse environments.

• Proficient in Python with experience in developing maintainable services, APIs, pipelines, or workflow automation.

• Familiarity with SQL and relational databases like PostgreSQL.

• Experience with cloud-based AI infrastructure, ideally with AWS and Amazon Bedrock.

• Strong skills in troubleshooting and root-cause analysis.

• Ability to collaborate with domain experts and transform ambiguous workflow requirements into scalable technical solutions.

• Excellent written and verbal communication skills in cross-functional settings.

🏝️ Benefits

• Comprehensive benefits package.

• Potential bonuses.

• Equity.

• Sales incentives.