Develop and enhance AI tools and agents that enhance internal productivity and automation across the organization.
Design and build scalable AI-powered solutions that provide repeatable, high-quality outputs to complex internal business processes.
Deploy custom AI agents that interact with internal datasets and APIs using platforms and services such as Azure AI, OpenAI services, and/or self-hosted (local) LLMs.
Build automation workflows and intelligent data pipelines across platforms such as Python, FastAPI/Flask, ServiceNow, n8n, Azure Logic Apps, and messaging/queue systems where relevant.
Collaborate with subject matter experts in AI/GenAI and internal teams to define requirements and turn them into functional prototypes and production-grade products.
Build and maintain full-stack applications and interfaces (e.g., React/TypeScript, Next.js) including real-time/streaming user experiences where useful (e.g., SSE/WebSockets).
Work dynamically in a fast-moving environment, exploring emerging AI approaches like vector search, RAG, grounding, evaluation/guardrails, and agent orchestration.
Contribute to innovation discussions, brainstorming sessions, and experimentation with new AI-driven ideas.
What we ask
Bachelor's or master's degree in computer science, Software Engineering, or related field, or equivalent practical experience.
Strong hands-on coding skills in Python, including experience with APIs, data handling, and AI workflows.
Experience building and deploying AI solutions using LLM frameworks and patterns (e.g., LangChain/LangGraph, function calling/tools, orchestration, prompt/versioning, evals).
Experience with frontend development using React and TypeScript (e.g., Next.js), ideally in component-based/modular architectures.
Experience with backend frameworks such as FastAPI, Flask, Node.js, and building well-structured services.
Understanding of API integration, authentication, and enterprise identity (OAuth2/OIDC, Azure AD/Entra ID), and secure microservice communication.
Knowledge of modern search and data technologies (e.g., Elasticsearch, Azure AI Search, GraphRAG, vector databases, hybrid retrieval, SQL/NoSQL).
Comfortable designing and developing automation flows and integrations (e.g., n8n, ServiceNow Flow Designer, Azure Logic Apps).
Proficient with Git/GitHub, containerization, and deployments (Docker, and optionally Kubernetes), and working in collaborative development environments.
Curious, proactive, and creative mindset; eager to build, test, break, and improve AI solutions through hands-on experimentation.
