AI Engineer

Purpose

As an AI Engineer, you’ll be a builder, deployer, and operator of AI/ML, Agentic AI, and GenAI solutions that deliver measurable outcomes across Clinisys from intelligent automation to advanced analytics and decision support. You’ll partner with product and IT teams to translate business problems into AI-powered solutions, ensuring they are secure, reliable, cost-effective, and aligned with responsible AI practices. You will also be an advocate for AI automation solutions across the business fostering innovation and adoption.

Clinisys' AI Philosophy

Building an AI-first organization is central to Clinisys’ purpose and the impact we deliver. As a global provider of intelligent diagnostic informatics solutions, we build AI-enabled, cloud-based platforms to enhance diagnostic workflows across healthcare, life sciences, and public health. By applying intelligent technology thoughtfully and responsibly, we help laboratories and test environments operate more effectively, generate meaningful insights at scale, and ultimately support healthier and safer communities. Operating across more than 30 countries, Clinisys expects all colleagues—regardless of role or function—to work confidently with AI-enabled tools, apply digital and analytical thinking, and continuously adapt as technologies evolve. We must drive an AI-first sense of purpose and urgency.

Essential Functions

· Build end-to-end AI agents and workflow automations from initial use-case scoping through deployment and ongoing maintenance.

· Write production Python code to integrate LLM APIs (prompt construction, response handling, context management, tool use) into internal workflows.

· Integrate AI tools with existing enterprise systems (NetSuite, HubSpot, M365, ServiceNow, etc.) via APIs with proper logging and monitoring.

· Establish reusable code patterns and component libraries to accelerate future agent development.

· Develop evaluation harnesses and model pipelines (training, evaluation, deployment) using AIOps practices to automate quality scoring and regression detection.

· Own deployed agent operations, including identity management, performance monitoring, human reinforcement workflows, and failure triaging.

· Optimize inference performance and cost through caching, batching, quantization, model selection, and workload management.

· Partner with Data Engineers to define feature requirements and create high-quality training and validation datasets.

· Apply responsible AI controls (privacy, security, governance) and collaborate with Security/Compliance to meet regulatory expectations.

· Maintain technical documentation, runbooks, and operational procedures for production AI services.

· Communicate project status, outcomes, and technical complexities clearly to both technical and non-technical stakeholders.

Required Experience and Education

· Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent work experience.

· Proven experience (5+ years) building production software systems, with at least 2+ years delivering AI/ML or GenAI solutions.

· Strong software engineering fundamentals (APIs, testing, CI/CD, observability) and proficiency in Python and/or another relevant language.

· Experience with ML frameworks and tooling (e.g., PyTorch/TensorFlow-like concepts) and/or GenAI stacks (LLM APIs, vector databases, orchestration).

· Knowledge of AIOps practices (model registry, experiment tracking, deployment strategies, monitoring) and responsible AI principles.

· Ability to communicate clearly with both technical and non-technical stakeholders; comfortable iterating quickly in ambiguous problem spaces.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.