Senior Data Scientist (Agentic AI Platform)

What you will do We are hiring a Senior Data Scientist to play a key role in building our Agentic AI Platform — a system of autonomous, tool-using AI agents that plan, reason, and execute complex business workflows end-to-end. The ideal candidate combines strong ML fundamentals with hands-on experience in LLM-based application development, agent orchestration frameworks, and Microsoft Azure cloud services. You will architect and ship production-grade agentic solutions, mentor junior team members, and set technical direction for GenAI initiatives across the organization. How you will do it Design, build, and productionize multi-agent systems — including planning, tool calling / function calling, memory, and orchestration — using frameworks such as LangGraph, AutoGen, CrewAI, or Semantic Kernel. Develop RAG pipelines end-to-end: document ingestion, chunking strategies, embeddings, vector search (Azure AI Search / FAISS / pgvector), re-ranking, and grounding for agent knowledge. Integrate agents with enterprise systems and APIs via tool/function calling and Model Context Protocol (MCP) or similar connector patterns. Build and maintain LLM evaluation frameworks for agentic workflows — task-completion metrics, hallucination detection, trajectory analysis, LLM-as-judge pipelines, and A/B testing. Implement guardrails, safety, and governance for agents: prompt-injection defense, content filtering, role-based tool permissions, human-in-the-loop checkpoints, and audit logging. Fine-tune and optimize LLMs where needed (LoRA/PEFT, prompt optimization, model routing, latency/cost trade-offs) on Azure OpenAI / Azure AI Foundry. Design, build, and evaluate classical ML models (classification, regression, forecasting, NLP) where they complement agentic workflows. Own LLMOps/MLOps for the platform: experiment tracking, prompt versioning, CI/CD, observability and tracing (LangSmith, Azure Monitor, OpenTelemetry), drift monitoring, and retraining strategies. Collaborate with data engineers on data quality, availability, and governance across Azure Data Lake, Databricks, and Synapse Analytics. Translate ambiguous business problems into agentic AI solutions; present architecture decisions and results to senior stakeholders. Mentor junior data scientists, lead code/design reviews, and champion engineering best practices. Required Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field. 4–5 years of professional experience in data science / ML, with at least 1–2 years building LLM or GenAI applications in production. Hands-on experience with agentic frameworks: LangChain/LangGraph, AutoGen, CrewAI, Semantic Kernel, or equivalent (at least one in production). Strong understanding of LLM application patterns: prompt engineering, function/tool calling, structured outputs, RAG, agent memory, and multi-agent orchestration. Expert-level Python (pandas, NumPy, scikit-learn, async programming, API development with FastAPI). Hands-on experience with Azure services: Azure OpenAI / AI Foundry, Azure ML, Azure AI Search, Azure Databricks, Azure Data Factory, or Synapse. Experience with vector databases and embeddings (Azure AI Search, Pinecone, Weaviate, Qdrant, FAISS, or pgvector). Solid grounding in classical ML: supervised/unsupervised learning, model evaluation, and hyperparameter tuning; experience with TensorFlow or PyTorch. Strong SQL skills and experience working with large-scale data. Proven MLOps/LLMOps experience: MLflow, prompt/model versioning, CI/CD (Azure DevOps or GitHub Actions), and production monitoring. Ability to evaluate and mitigate LLM-specific risks: hallucination, prompt injection, data leakage, and cost/latency constraints. Preferred Experience with Model Context Protocol (MCP), OpenAI Assistants/Agents SDK, or Anthropic tool-use APIs. Microsoft certifications: AI-102 (Azure AI Engineer), DP-100 (Azure Data Scientist Associate). Experience fine-tuning open-source LLMs (Llama, Mistral, Phi) using LoRA/QLoRA and serving via vLLM or Azure ML endpoints. Familiarity with observability/tracing for agents: LangSmith, Langfuse, Arize Phoenix, or OpenTelemetry. Knowledge of containerization and deployment: Docker, Kubernetes (AKS), Azure Container Apps. Big data experience with Apache Spark (PySpark) via Azure Databricks. Experience with knowledge graphs, graph RAG, or semantic layers for agent grounding. Contributions to open-source GenAI/agentic projects or published technical content. What We Offer Competitive salary and performance-based incentives. Opportunity to architect a greenfield agentic AI platform from the ground up. Azure and AI certification sponsorship plus a continuous learning budget. Technical leadership pathway and mentorship opportunities. Access to cutting-edge GenAI tooling, compute, and cross-domain AI projects. Flexible hybrid working model and collaborative culture. Our salary and benefits The initial basic salary for this position will be in the range of €2,430 - €3,807 per month, plus a 13th month salary applied after your first 6 months in the job. The final package will reflect your experience, skills, and qualifications relevant to the role. We are committed to fair, equitable, and gender-neutral pay practices. At Johnson Controls, your work comes with benefits that support both your career and your wellbeing. Meal vouchers fully covered by the company. Flexible benefits budget with access to 3,500+ options, including a MultiSport card, medical and wellness services. Extra savings through retail and lifestyle discounts (Benefit+). Allowance for the private kindergarten or nursery to support your family. Flexible working hours and home office days. Allowance for language courses, professional development support, and wellbeing support. On site benefits: massages, distribution of fruits, yoga, psychologist, health month, various events with supporting groups (volunteering activities, branding activities). Seniority benefits - extra monthly financial allowance, medical care and support, wellbeing day. Relocation support with housing allowance if moving to Slovakia About Us Johnson Controls, a global leader in thermal management, mission-critical building systems, energy efficiency, and decarbonization, helps customers use energy more productively, reduce carbon emissions, and operate with the precision and resilience required in rapidly expanding industries such as data centers, healthcare, pharmaceuticals, advanced manufacturing, and higher education. For more than 140 years, Johnson Controls has delivered performance where it really matters. Backed by advanced technology, lifecycle services and an industry-leading field organization, we elevate customer performance, turn goals into real-world results and help move society forward. We are committed to diversity and inclusion and believe that different perspectives make us stronger. By encouraging open dialogue and valuing individuality, we strive to be one of the most desirable places to work. #LI-Hybrid #LI-JT1 Johnson Controls: Enhancing the Intelligence of Buildings Your buildings have a purpose. They are places for people to live or work. Facilities for learning or healing. Venues for entertainment and shopping. Sites for the specialized storage of tangible goods or mission-critical data. Your buildings have a huge variety of functions; they are central to your mission. This is where Johnson Controls comes in, helping drive the outcomes that matter most. Through a full range of systems and digital solutions, we make your buildings smarter. A smarter building is safer, more comfortable, more efficient, and, ultimately, more sustainable. Most important, smarter buildings let you focus more intensely on your unique mission. Better for your people. Better for your bottom line. Better for the planet. At Johnson Controls, we’ve been making buildings smarter since 1885, and our capabilities, depth of innovation experience, and global reach have been growing ever since. Today, we offer the world’s largest portfolio of building products, technologies, software, and services; we put that portfolio to work to transform the environments where people live, work, learn and play.