AI Engineer at Clario designing AI-powered applications for clinical research. Collaborating with cross-functional teams to build innovative software 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
Competitive compensation
Attractive benefits (security, flexibility, support and well-being)
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