Data Scientist / AI Solution Engineer

Responsibilities: 

AI
& Agentic Application Development

·       Design, develop, and deploy AI-powered applications using
LLMs and Agentic AI architectures.

·       Build reliable AI workflows utilizing tool/function calling,
structured outputs, memory management, state handling, and error recovery.

·       Implement and maintain production AI systems with strong
focus on scalability, observability, security, and reliability.

·       Leverage AI-assisted development tools for coding, code
review, testing, and validation.

·       Define and execute AI evaluation frameworks, including
experimentation, model assessment, performance measurement, and statistical
analysis.

Python
Engineering & API Development

• Develop high-quality,
  maintainable Python applications following software engineering best
  practices.
  
• Build and maintain RESTful
  APIs using FastAPI.
  
• Implement API contracts,
  request/response validation using Pydantic, and streaming responses.
  
• Develop automated test
  suites and maintain CI/CD pipelines.
  
• Apply asynchronous
  programming techniques to improve application performance and
  scalability.
  

RAG,
LLMs & Machine Learning

• Design and implement
  Retrieval-Augmented Generation (RAG) solutions.
  
• Optimize chunking
  strategies, embeddings, hybrid retrieval, reranking, and retrieval
  quality.
  
• Evaluate and improve AI
  system performance using quantitative metrics.
  
• Apply machine learning
  techniques to predictive and prescriptive business problems.
  
• Demonstrate strong
  understanding of LLM architecture, tokenization, embeddings,
  transformers, attention mechanisms, and model limitations.
  

Data
& Business Translation

• Translate business
  requirements into measurable technical solutions and acceptance
  criteria.
  
• Design and optimize data
  models for SQL and NoSQL databases.
  
• Work with Cosmos DB and
  other scalable data platforms.
  
• Collaborate with product,
  business, and engineering teams to deliver end-to-end solutions.
  

Azure
AI & Cloud Solutions

• Design AI solutions
  utilizing:
  
• Azure AI Foundry
  
• Azure AI Search
  
• Azure OpenAI / LLM
  Services
  
• Azure Functions
  
• Azure Cosmos DB
  
• Azure Blob Storage
  
• Deploy, monitor,
  troubleshoot, and optimize AI applications on Azure.
  

Profile Description: 

• 10+ years of software
  engineering experience, with 5-6+ years focused on AI, GenAI, LLMs, and
  cloud-native application development.
  
• Strong Python expertise
  with proven experience in building scalable, maintainable, and
  well-tested applications.
  
• Hands-on experience
  developing APIs using FastAPI, Pydantic, asynchronous programming, and
  streaming responses.
  
• Proven track record
  delivering production-grade AI solutions, including deployment,
  monitoring, troubleshooting, and operational support.
  
• Experience building
  Agentic AI applications using tool/function calling, structured outputs,
  workflow orchestration, memory, and state management.
  
• Strong understanding of
  RAG architectures, embeddings, hybrid search, reranking, and retrieval
  evaluation.
  
• Solid foundation in
  machine learning, statistics, experimentation, and AI model evaluation.
  
• Deep understanding of LLM
  concepts, including tokenization, embeddings, transformers, attention
  mechanisms, and model limitations.
  
• Experience implementing AI
  safety, observability, prompt-injection protection, and data governance
  practices.
  
• Hands-on experience with
  LangGraph or similar orchestration frameworks.
  
• Strong knowledge of SQL
  and NoSQL databases, including Cosmos DB and data modeling best
  practices.
  
• Experience working with
  Azure AI Foundry, Azure AI Search, Azure OpenAI, Azure Functions, Blob
  Storage, and related Azure services.
  
• Ability to translate
  business requirements into measurable outcomes and scalable technical
  solutions.
  
• Familiarity with CI/CD,
  Agile/Scrum methodologies, and modern software engineering practices.
  
• Strong problem-solving,
  communication, stakeholder management, and collaboration skills.
  
• Demonstrates ownership,
  continuous learning, knowledge sharing, and a passion for engineering
  excellence.
  
• Exposure to Polars, Kedro,
  Grafana, advanced data engineering, and advanced machine learning
  techniques is a plus.
  

Nice to have
Competencies: 

• Working experience in a SAFe
  environment is a plus.
  
• Experience working with European
  clients