Senior 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,pyspark,vector database,chunking strategies,rag,langchain