Expert Software Engineer I

Alegeus; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Flexible work environment

Competitive salaries

Professional development

Health, wellness, and financial packs

Job summary

Alegeus is building an AI Enablement Engineering Team to integrate AI capabilities into its core fintech-healthcare products. As a Software Engineer, you will implement AI-driven features, APIs, and data pipelines, collaborating with product, data science, and platform teams to deliver production-ready solutions.

You will work with SLMs/LLMs, cloud-hosted and on-premise variants, and apply robust MLOps, CI/CD, and observability practices across the stack.

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).

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.

Skills

Python

SQL

Pandas

NumPy

TensorFlow

PyTorch

Scikit-learn

ML Ops

Azure ML

Docker

Kubernetes

C#

ASP.NET Core

REST APIs

LLMs

SLMs

RAG

MCP

Tools

Docker

Kubernetes

Azure ML

MLflow

Job description

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.

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.

Key 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).

Preferred Qualifications

• 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 monitoring, cost optimization, and production-level inference tuning.
• Exposure to healthcare IT or healthcare data standards such as claims processing, HL7, EDI 837, EDI 835, or FHIR.
• Familiarity with feature stores, vector databases, and reusable ML components for cross-product AI enablement.
• Strong communication and collaboration skills, with the ability to work across global engineering and product teams.

Why Join Alegeus?

• Drive meaningful innovation by integrating AI into healthcare financial solutions.
• Collaborate with talented engineers and AI experts across foundational and product teams.
• Take ownership of high-impact features that directly enhance customer experience.

Be part of a forward-thinking organization committed to AI-led transformation.

BECAUSE WE CARE, WE OFFER:

• A flexible work environment
• Competitive salaries, paid vacation, and holidays
• Robust professional development programs
• Comprehensive health, wellness, and financial packages

SHARED AMBITION. INSPIRED FUTURE.

At Alegeus, our success is guided by our aligned vision and values—it is how we work together and collaborate to achieve our goals.

• People First. We pride ourselves in bringing talented people together and treating one another with care.
• Partner Powered. We are committed to empowering our partners, knowing our success is shared and we win as one.
• Always Advancing. We are driven by potential and relentlessly determined to achieve our goals.

"I truly believe that people who are well-skilled and talented can go wherever they want in this company. We want to create the best place anyone has ever worked." - Alegeus employee

We are committed to a policy of Equal Employment Opportunity and will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin or ancestry, sex, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, marital status, or any other legally recognized protected basis under federal, state or local laws, regulations or ordinances. The information collected by this application is solely to determine suitability for employment, verify identity and maintain employment statistics on applicants.

At Alegeus, being transparent about our compensation philosophy and approach is more than just a legal requirement. As our organization continues to grow and evolve, we have made a commitment to ensure that our compensation framework is equitable, data-driven, consistent, and unbiased, with allowable pay differences based on factors unique to each candidate (think: skills, experience, qualifications, etc.) in order to attract and retain a highly talented and committed workforce.

We are taking an "inside-out" approach to pay transparency by first educating our valued managers and internal workforce and then moving to publishing compensation ranges externally. In the interim, if you are a California, Colorado, Connecticut, Maryland, Nevada, New Jersey, New York, Ohio or Washington resident and this role is physically available in your state or classified as remote, you may be eligible to receive additional information about the compensation and benefits for this role, which we will provide upon request. Please send an email identifying the title of the role you are interested in and the state you reside in to [e-mail].