Data Scientist
Posted Updated
Description
Job_Description":"
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
- Working experience in a SAFe environment is a plus.
- 10+ years of software engineering experience, with 5-6+ years focused on AI, GenAI, LLMs, and cloud-native application development.
- Design AI solutions utilizing:
- Translate business requirements into measurable technical solutions and acceptance criteria.
- Design and implement Retrieval-Augmented Generation (RAG) solutions.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Skills
- Acceptance Criteria
- Agentic AI
- Agile
- AI
- API
- Azure
- Azure Functions
- CI/CD
- Cloud
- Cloud Native
- Cosmos Db
- Data Engineering
- Data Governance
- Data Modeling
- Embeddings
- FastAPI
- Generative AI
- Grafana
- LangGraph
- LLM
- Machine Learning
- Model Evaluation
- NoSQL
- Observability
- OpenAI
- Polars
- Pydantic
- Python
- RAG
- REST
- Scrum
- SQL
- Stakeholder Management
- Statistics
- Transformers
- Workflow Orchestration