Expert Software Engineer I

About the role

We are forming an AI Enablement Engineering Team-focused on integrating foundational AI capabilities (such as document extraction and LLM-based chatbot services) into our core products. This team will work closely with product domain engineering teams and foundational AI teams to deliver end-to-end product features-like claims extraction built on our document intelligence service. As a Software Engineer in this team, you'll be expected to apply strong software engineering practices, leverage AI services, and work across integration points to bring intelligent automation into production systems.

Responsibilities

• Design, develop, and integrate AI-driven capabilities into scalable, production-grade healthcare platforms to improve automation, insights, and user experience.
• Build robust APIs, microservices, and integration layers that seamlessly connect AI and ML models with product workflows and enterprise systems.
• Apply strong data science skills including EDA, statistical analysis, hypothesis testing, advanced feature engineering, and model evaluation to shape and optimize ML solutions.
• Work hands-on with SLMs and LLMs, including locally hosted and cloud-deployed variants, optimizing performance, latency, and domain-specific use cases.
• Collaborate with foundational AI and platform teams to leverage reusable shared services such as extractors, conversational agents, embedding services, and retrieval pipelines.
• Use Python, SQL, Pandas, NumPy, TensorFlow, PyTorch, and Scikit-learn to build, evaluate, and deploy ML models across classification, forecasting, anomaly detection, and NLP use cases.
• Build and maintain ML pipelines for training, evaluation, deployment, monitoring, and retraining using MLOps tools and cloud-native patterns.
• Develop clean, reliable, and maintainable software leveraging Python, REST APIs, containers, and cloud-native engineering practices aligned with enterprise standards.
• Contribute to backend services using C# and ASP.NET Core to support AI workflows, platform integrations, and service orchestration.
• Collaborate effectively with Product Managers, Architects, Data Scientists, and Engineering teams to deliver end-to-end AI solutions.
• Adhere to engineering best practices across code quality, automated testing, CI/CD pipelines, observability, monitoring, and documentation.
• Participate in agile development sprints and contribute to sprint planning, reviews, retrospectives, and demos.
• Required Qualifications
• 6+ years of experience in AI engineering, ML engineering, data science, or software engineering within enterprise or SaaS environments.
• Proficient in Python, SQL, Pandas, NumPy, and modern ML frameworks such as TensorFlow, PyTorch, and Scikit-learn for data processing, feature engineering, model development, and evaluation.
• Strong experience applying ML algorithms including Random Forest, Gradient Boosting, logistic regression, anomaly detection, and advanced predictive modeling techniques.
• Hands-on experience in data science workflows including EDA, hypothesis testing, error analysis, statistical modeling, feature engineering, and model interpretation using techniques such as SHAP.
• MLOps experience with model training pipelines, experiment tracking, versioning, CI/CD for ML systems, monitoring, and deployment using Azure ML, MLflow, Docker, Kubernetes, or cloud inference endpoints.
• Experience building and operating end-to-end ML workflows from dataset creation and model training to deployment, monitoring, drift detection, and iterative improvements.
• Background in backend development using C# and ASP.NET Core for services, integrations, and API development supporting AI capabilities.
• Experience designing and consuming RESTful APIs for scalable and reliable communication across distributed and cloud-native systems.
• Familiarity with AI and ML technologies including LLMs, SLMs, embeddings, prompt engineering, retrieval pipelines, and AI service orchestration.
• Hands-on experience integrating backend services, ETL pipelines, data APIs, and enterprise data platforms to support analytics and AI solutions.
• Exposure to cloud platforms such as Azure, AWS, or GCP with working knowledge of cloud-native engineering and DevOps practices.
• Ability to explore and apply advanced AI techniques including Retrieval-Augmented Generation (RAG), Retrieval-Integrated Generation (RIG), Small Language Models (SLMs), and Model Context Protocol (MCP).

Requirements

• Experience integrating AI services such as OpenAI, Azure OpenAI, or Hugging Face models into production systems.
• Knowledge of document extraction, conversational systems, NLP pipelines, or multimodal AI workflows.
• Experience with ML observability, model moni

Benefits

Additional Information

Do you want to shape the future of fintech and healthtech ? Energized by challenges and inspired by bold goals? Ready to elevate your career alongside driven and talented colleagues? If that sounds like you, explore a career at Alegeus today. Opportunity Happens Here .

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