Data Scientist

• Design, develop, and maintain production-grade AI applications and services using modern software engineering practices (CI/CD, testing, observability, cloud-native design).
• Define and implement foundational platforms and tools (e.g., conversational bots, AI-powered search, unstructured data processing, GenBI) that are reusable and scalable across the enterprise.
• Participate in cross functional team initiatives-embedded projects with business stakeholders-to rapidly build and deploy AI solutions that solve high-priority business problems.
• Evaluate and integrate existing AI tools, frameworks, and APIs (e.g., LLMs, vector DBs, retrieval-augmented generation, AI agents) into robust applications.
• Champion automation in workflows-from data management ingestion and pre-processing to evaluation, to model integration and deployment.
• Collaborate with data scientists, product managers, and other engineers to ensure end-to-end delivery and reliability of AI products.
• Stay current with emerging AI technologies but prioritize practical application and delivery over experimental research.
• Contribute to the internal knowledge base, tooling libraries, and documentation to scale AI engineering best practices across the organization.

Do you have experience in Python?, Do you have a Master's degree?, * Professional software engineering experience: ability to independently design and ship complex systems in production.

• Strong programming skills in Python (preferred), Java, or similar languages, with experience in developing microservices, APIs, and backend systems.
• Strong problem-solving skills and the ability to balance engineering rigor with delivery speed.
• Solid understanding of software architecture, cloud infrastructure (AWS, Azure, or GCP), and modern DevOps practices.
• Experience integrating machine learning models into production systems (e.g., LLMs via APIs, fine-tuning, RAG patterns, embeddings, agents and crew of agents etc.).
• Ability to move quickly while maintaining code quality, test coverage, and operational excellence. Preferred:
• Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems.
• Hands-on experience with Retrieval Augmented Generation applications, AI agents and systems built around them.
• Experience using GenAI frameworks such as LlamaIndex, Crew AI, AutoGen, or similar agentic/LLM orchestration toolkits.
• Exposure to working with unstructured data (documents, conversations, images) and transforming it into usable structured formats.
• Experience building chatbots, search systems, or generative AI interfaces.
• Background in working within platform engineering or internal developer tools teams.
• Prior experience working in an embedded (forward-deployed) team model with business stakeholders.
• Experience building production grade, reliable AI applications