Data Scientist

We're looking for engineers who think holistically, automate relentlessly, and are fluent in the fast-moving world of AI tooling and infrastructure-but grounded in disciplined, · 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 preprocessing 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?, We're looking for individuals who thrive at the intersection of disciplined software development and modern AI applications. You should be comfortable working across the full lifecycle of a product-from ideation and architecture to deployment and automation-while navigating ambiguity and driving toward execution. Strong systems thinking, ownership mindset, and the ability to ship value fast are essential., · 5+ years of 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