Senior Principal Software Engineer - R&D Tech

• 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

Cloud Architecture & Services

• 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

Data Engineering

• 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

AI/ML & GenAI Integration

• 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

Database & Data Management

• 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

DevOps & Infrastructure

• 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

Cross-team Collaboration

• 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

We are looking for professionals with these required skills to achieve our goals:

• Bachelor's degree in Computer Science or equivalent relevant industry experience
• Significant hands-on software development experience with demonstrated progression in technical complexity
• Expert-level Python programming with extensive production application development experience
• Strong full-stack development experience with modern frameworks:

• Backend: Python (FastAPI, Flask, Django)
• Frontend: React, Next.js, TypeScript, or similar modern frameworks

• Cloud services experience, preferably Azure (App Services, Functions, Storage, or equivalent cloud services)
• Strong SQL skills: Writing complex queries, data modeling, and optimization
• Data engineering fundamentals: Building data pipelines and working with large datasets
• 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

• Experience building production-grade applications: Scalable, maintainable, well-tested code
• Understanding of software architecture: Design patterns, microservices, distributed systems, cloud-native architectures
• Version control with Git and collaborative development workflows
• DevOps practices: CI/CD pipelines, containerization basics
• Agile development practices and iterative development
• Excellent problem-solving and debugging skills
• Strong communication and collaboration skills
• 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:

If you have the following characteristics, it would be a plus:

• 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

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