Senior Python Engineer/ Data Scientist

Company: Papigen

Location: Remote

Experience: 6+ Years

About The Role Papigen is seeking an experienced

Senior Python Engineer / GenAI Platform Engineer to serve as the critical technical bridge between research-driven AI proof-of-concepts and scalable, production-grade enterprise solutions. This role focuses on transforming AI agents and workflows developed by data scientists into robust, secure, and maintainable applications using

Python, LangGraph, Azure Functions, and Durable Functions . The ideal candidate will have deep expertise in backend engineering, workflow orchestration, cloud-native development on Azure, and productionizing Generative AI solutions. Key Responsibilities AI Workflow Productionization

• Translate AI agents, workflows, and proof-of-concept solutions developed by the Data Science team into production-ready Python services.
• Design, implement, and maintain scalable AI agent orchestration workflows using LangGraph, LangChain, or similar frameworks.
• Ensure workflow correctness, reliability, observability, and extensibility. Azure Cloud Development
• Develop and manage Azure Functions and Azure Durable Functions leveraging orchestrator and activity patterns.
• Build and optimize long-running, stateful, and event-driven GenAI workflows.
• Integrate AI solutions with existing backend platforms, APIs, and enterprise systems. Backend & API Engineering
• Design and develop high-performance APIs using FastAPI or similar Python frameworks.
• Build and maintain scalable data pipelines supporting AI and ML workflows.
• Ensure seamless communication between AI services, databases, APIs, and external systems. Production Engineering & Reliability
• Implement robust error handling, retry mechanisms, idempotency, fault tolerance, and resiliency patterns.
• Drive observability through logging, monitoring, tracing, and performance metrics.
• Optimize resource utilization, throughput, and execution efficiency across workflows and services. Collaboration & Software Delivery
• Partner closely with Data Scientists to understand model behavior, assumptions, and limitations.
• Participate throughout the Software Development Lifecycle (SDLC), including design, development, testing, deployment, and production support.
• Conduct code reviews and contribute to engineering best practices and coding standards.
• Support security hardening, compliance initiatives, and operational excellence. Agile Participation
• Actively contribute to sprint planning, standups, backlog refinement, retrospectives, and release planning.
• Work collaboratively across global and multicultural teams operating across multiple time zones.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• 6+ years of professional software engineering experience with strong expertise in Python development.
• Proven experience building and operating production-grade backend systems and distributed services.
• Hands-on experience with: + Python + Azure Functions + Azure Durable Functions + FastAPI (or equivalent API frameworks) + LangGraph, LangChain, or similar agent orchestration frameworks
• Strong understanding of: + Generative AI systems and ML pipelines + AI/ML productionization lifecycle + Workflow orchestration patterns + Distributed systems and microservices architecture
• Experience with Python ecosystem libraries such as: + NumPy + Pandas + Scikit-learn
• Strong knowledge of production engineering concepts: + Error handling + Retry mechanisms + Idempotency + Observability + Logging & Monitoring + Fault tolerance
• Experience with Git-based version control and CI/CD pipelines.
• Excellent debugging, troubleshooting, and performance optimization skills.
• Strong communication and stakeholder management abilities.

Preferred Qualifications

• Experience deploying and managing GenAI solutions in Azure environments.
• Knowledge of Azure OpenAI Services and AI agent architectures.
• Experience working with vector databases, RAG architectures, and LLM-powered applications.
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Exposure to MLOps and AI platform engineering practices.
• Experience supporting security audits, compliance requirements, and cloud governance initiatives. Technical Skills

Programming & Frameworks

• Python
• FastAPI
• LangGraph
• LangChain

Cloud & Infrastructure

• Microsoft Azure
• Azure Functions
• Azure Durable Functions

AI / Data Technologies

• Generative AI
• Machine Learning Pipelines
• NumPy
• Pandas
• Scikit-learn

DevOps & Engineering

• CI/CD Pipelines
• Git
• Monitoring & Logging
• API Development
• Workflow Orchestration What Success Looks Like
• Successfully productionizing AI prototypes into enterprise-grade solutions.
• Delivering reliable, scalable, and observable AI workflows.
• Improving performance, maintainability, and operational excellence of GenAI platforms.
• Enabling seamless collaboration between Data Science and Engineering teams.
• Driving engineering best practices and reducing technical debt across AI initiatives.

Employment Type: Full-Time

Location: Remote

Experience Level: Senior (6+ Years)

Industry: AI / Generative AI / Cloud Engineering / Software Development Skills: generative ai,python,azure,ai,llm,genai