Expert Software Engineer I
Alegeus Technologies LLC8 months ago
Bengaluru, IndiaEntry Level
Responsibilities
- Design, develop, and integrate AI-driven capabilities into scalable healthcare platforms.
- Build APIs, microservices, integration layers, and backend services connecting AI and ML models with product workflows.
- Perform exploratory data analysis, statistical analysis, hypothesis testing, feature engineering, model evaluation, and model interpretation.
- Develop, evaluate, deploy, monitor, and retrain ML models for classification, forecasting, anomaly detection, and NLP use cases.
- Work with locally hosted and cloud-deployed LLMs and SLMs to optimize performance, latency, and domain-specific applications.
- Integrate shared services including document extractors, conversational agents, embedding services, and retrieval pipelines.
- Build and maintain end-to-end ML pipelines using MLOps tools and cloud-native patterns.
- Contribute to C# and ASP.NET Core backend services supporting AI workflows, integrations, and service orchestration.
- Design and consume RESTful APIs and integrate backend services, ETL pipelines, data APIs, and enterprise data platforms.
- Apply engineering practices involving automated testing, CI/CD, observability, monitoring, documentation, and agile delivery.
Requirements
- Require 6+ years of experience in AI engineering, ML engineering, data science, or software engineering in enterprise or SaaS environments.
- Require proficiency in Python, SQL, Pandas, NumPy, TensorFlow, PyTorch, and Scikit-learn.
- Require experience with ML algorithms including Random Forest, Gradient Boosting, logistic regression, anomaly detection, and predictive modeling.
- Require experience with EDA, hypothesis testing, error analysis, statistical modeling, feature engineering, model interpretation, and SHAP.
- Require MLOps experience covering training pipelines, experiment tracking, versioning, CI/CD, monitoring, deployment, and model lifecycle management.
- Require experience with Azure ML, MLflow, Docker, Kubernetes, or cloud inference endpoints.
- Require backend development experience with C#, ASP.NET Core, RESTful APIs, distributed systems, and cloud-native architectures.
- Require familiarity with LLMs, SLMs, embeddings, prompt engineering, retrieval pipelines, RAG, RIG, and MCP.
- Require exposure to Azure, AWS, or GCP and cloud-native engineering and DevOps practices.
- Prefer experience integrating OpenAI, Azure OpenAI, or Hugging Face models into production systems.
- Prefer knowledge of document extraction, conversational systems, NLP pipelines, multimodal AI, ML observability, model monitoring, cost optimization, and inference tuning.
- Prefer exposure to healthcare IT and standards including claims processing, HL7, EDI 837, EDI 835, and FHIR.
- Prefer familiarity with feature stores, vector databases, reusable ML components, and cross-product AI enablement.
Benefits
- Flexible work environment.
- Competitive salaries, paid vacation, and holidays.
- Professional development programs.
- Health, wellness, and financial packages.
Tech Stack
AWSAzureC#DockerGoogle Cloud PlatformKubernetesMLflowNumPyPandasPythonPyTorchscikit-learnSQLTensorFlow
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