Technical lead building safe, evaluable LLM agents and AI infrastructure for OpenLoop’s telehealth platform. Setting architecture, observability, retrieval, and model operations direction.
About the role
- AI Engineer designing AI-powered applications and systems for pharmaceutical and healthcare sectors. Collaborating in a global team to drive innovation in AI and machine learning solutions.
Responsibilities
- Design, develop, and maintain AI-powered applications with a strong focus on Agentic AI, AI Agents, and LLM-enabled workflows
- Build software services, APIs, and orchestration layers that connect AI models and tools into scalable production solutions
- Contribute to the design, training, fine-tuning, evaluation, and deployment of AI models, including large language models and supporting ML components
- Develop and optimize data pipelines for model training, retrieval, evaluation, and monitoring
- Implement testing strategies, benchmarks, and quality controls to ensure AI systems are reliable, accurate, secure, and performant
- Collaborate with AI engineers, software developers, scientists, and product managers to translate business requirements into technical solutions
- Participate in the full software development lifecycle: design, implementation, testing, deployment, and monitoring in cloud environments (AWS preferred)
- Apply engineering best practices for code quality, documentation, maintainability, and operational excellence
- Support experimentation with new AI techniques, frameworks, and tooling, and help mature promising ideas into production capabilities
- Stay up to date with advancements in generative AI, agentic systems, multi-modal AI, and cloud engineering.
Requirements
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field (Master's a plus)
- 3+ years of experience in software engineering, AI engineering, machine learning, or a related technical field
- Strong proficiency in Python and experience with AI/ML frameworks such as PyTorch or TensorFlow
- Experience building AI-enabled software applications and integrating machine learning or LLM capabilities into backend systems
- Hands-on experience or strong interest in Agentic AI, AI Agents, tool-use workflows, or multi-step orchestration patterns
- Familiarity with model training, fine-tuning, evaluation, prompt and workflow design, or model-serving concepts
- Understanding of cloud-based architectures
- Strong problem-solving, communication, and collaboration skills
- Commitment to code quality, security, scalability, and performance
- Eagerness to learn, adapt, and stay current with emerging AI technologies and engineering practices.
Benefits
- health insurance
- retirement plans
- paid time off
- flexible work arrangements
- professional development
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