Senior Principal Software Engineer - R&D Tech

Role Summary

Senior Principal Software Engineer with broad expertise across software development, data engineering, cloud architecture, and AI/ML technologies. This is a hands-on technical role where you'll spend the majority of your time writing code, building data pipelines, architecting cloud-native solutions, and integrating AI/ML capabilities into production applications. You’ll be a versatile engineer who can work across the full stack, understand data flows, leverage cloud services effectively, and apply AI/ML techniques to solve real-world problems.

Responsibilities

• Write production-grade code for full-stack applications using Python and modern frontend frameworks
• Build and maintain scalable REST APIs and microservices architectures
• Design application architectures and implement technical solutions
• Develop user interfaces and data visualization components
• Write comprehensive tests and ensure code quality
• Debug and optimize application performance
• Design and architect cloud-native applications and solutions on Azure
• Leverage Azure services including App Services, Azure Functions, AKS, Storage, Data Factory, Cosmos DB
• Implement scalable, resilient, and cost-effective cloud architectures
• Optimize cloud resource utilization and performance
• Design for high availability, disaster recovery, and security
• Implement cloud security best practices and governance
• Build and maintain data pipelines for large-scale data processing
• Implement ETL/ELT processes for diverse data sources
• Optimize data workflows and processing performance
• Design and implement data models and schemas
• Work with structured and unstructured data at scale
• Integrate AI/ML models and APIs into production applications
• Build GenAI applications using LLMs and frameworks like LangChain
• Implement RAG (Retrieval Augmented Generation) architectures
• Work with vector databases for semantic search capabilities
• Apply prompt engineering techniques for optimal LLM performance
• Understand and implement basic NLP tasks (text classification, entity extraction, embeddings)
• Collaborate with data scientists to productionize ML models
• Evaluate and integrate new AI/ML technologies
• Write SQL queries for data analysis and application needs
• Design and optimize database schemas for both relational and NoSQL databases
• Tune query performance and implement indexing strategies
• Implement data access patterns and ORM frameworks
• Implement Infrastructure as Code and CI/CD pipelines
• Containerize applications and orchestrate deployments with Docker and Kubernetes
• Implement monitoring, logging, and alerting solutions
• Automate deployment and operational processes
• Ensure application scalability and reliability
• Work closely with data scientists, engineers, and product owners across R&D
• Participate in code reviews and knowledge sharing
• Contribute to technical discussions and solution designs
• Identify innovations and architect solutions
• Evaluate and integrate new technologies

Qualifications

• Required: Bachelor's degree in Computer Science or equivalent relevant industry experience
• Required: Significant hands-on software development experience with demonstrated progression in technical complexity
• Required: Expert-level Python programming with extensive production application development experience
• Required: Strong full-stack development experience with modern frameworks:
  • Backend: Python (FastAPI, Flask, Django)
  • Frontend: React, Next.js, TypeScript, or similar modern frameworks
• Required: Cloud services experience, preferably Azure (App Services, Functions, Storage, or equivalent cloud services)
• Required: Strong SQL skills: Writing complex queries, data modeling, and optimization
• Required: Data engineering fundamentals: Building data pipelines and working with large datasets
• Required: Understanding of AI/ML concepts and practical experience:
  • Familiarity with LLMs and GenAI applications
  • Basic understanding of how to integrate AI/ML APIs into applications
  • Knowledge of prompt engineering basics
  • Understanding of RAG architectures or willingness to learn quickly
• Required: Experience building production-grade applications: Scalable, maintainable, well-tested code
• Required: Understanding of software architecture: Design patterns, microservices, distributed systems, cloud-native architectures
• Required: Version control with Git and collaborative development workflows
• Required: DevOps practices: CI/CD pipelines, containerization basics
• Required: Agile development practices and iterative development
• Required: Excellent problem-solving and debugging skills
• Required: Strong communication and collaboration skills
• Required: Ability to quickly learn and adapt to new technologies

• Highly Desired Skills: Azure cloud platform expertise: Deep knowledge of Azure services (App Services, Azure Functions, AKS, Storage Accounts, Azure Data Factory, Cosmos DB, Azure SQL, Key Vault, Application Insights)
• Cloud architecture and design: Designing scalable, secure, and cost-effective cloud solutions
• Databricks and Apache Spark for large-scale data processing
• Hands-on experience with GenAI platforms: OpenAI, Azure OpenAI, LangChain, or similar frameworks
• Experience building RAG applications with chunking, vectorization, retrieval strategies
• Vector databases: pgvector, Pinecone, Weaviate, or similar
• DevOps maturity: Infrastructure as Code (Terraform, Bicep, ARM templates), advanced CI/CD
• Containerization and orchestration: Docker and Kubernetes (AKS)
• Database expertise: PostgreSQL, SQL Server, Azure SQL with performance tuning
• Cloud security: Identity management, RBAC, network security, encryption
• Azure DevOps or GitHub Actions for CI/CD pipelines
• Experience with REST API design and microservices patterns

• Preferred Qualifications: Azure certifications (Azure Solutions Architect, Azure Developer, Azure Data Engineer)
• Advanced AI/ML knowledge:
  • Experience with ML frameworks (TensorFlow, PyTorch, Hugging Face)
  • Understanding of model training and evaluation
  • Knowledge of NLP techniques beyond basic text processing
  • Experience with multi-agent systems or advanced RAG patterns
• MLOps knowledge: Model deployment, versioning, monitoring, A/B testing
• Azure AI services: Document Intelligence, Cognitive Search, Azure AI Studio, Azure Machine Learning
• Search technologies: Azure Search, Sinequa, Elasticsearch, Lucene-based systems
• Advanced Spark optimization and performance tuning
• Real-time data processing and streaming architectures (Kafka, Azure Event Hubs)
• Pharmaceutical, healthcare, or regulated industry experience
• Experience with compliance requirements: HIPAA, GxP, 21 CFR Part 11
• Experience with data visualization libraries (D3.js, Plotly, Chart.js)
• Software security best practices and secure coding
• FinOps practices: Cloud cost optimization and management
• Experience mentoring junior engineers

Education

• Bachelor's degree in Computer Science or equivalent relevant industry experience