Senior Data Scientist (Agentic AI Platform)
Reads like a ML Engineer role: putting models into production.
Lisbon-Lisbon-Portugal
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Azure and AI certification sponsorship plus a continuous learning budget.
Read the full posting
What you’ll work on
Full postingDesign, build and productionize multi-agent systems with planning, tool calling and memory
Develop end-to-end RAG pipelines, from document ingestion to vector search and re-ranking
Integrate agents with enterprise systems and APIs via tool calling and MCP connectors
Build and maintain LLM evaluation frameworks for agentic workflows
Implement guardrails, safety and audit logging for agents
From the employer’s posting
Design, build, and productionize multi-agent systems — including planning, tool calling / function calling, memory, and orchestration
Develop RAG pipelines end-to-end: document ingestion, chunking strategies, embeddings, vector search
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
Implement guardrails, safety, and governance for agents: prompt-injection defense, content filtering, role-based tool permissions, human-in-the-loop checkpoints, and audit logging.
Tools in this posting
- Python
- SQL
- Azure
- Databricks
- FastAPI
- NumPy
- pandas
- scikit-learn
Source — Tool mentions in context
- Strong understanding of LLM application patterns including prompt engineering - Expert-level Python (pandas, NumPy, scikit-learn, async programming, API development with FastAPI). - Experience with vector databases and embeddings (Azure AI Search, Pinecone, Weaviate, Qdrant, FAISS, or pgvector).
- Experience with vector databases and embeddings (Azure AI Search, Pinecone, Weaviate, Qdrant, FAISS, or pgvector). - Strong SQL skills and experience working with large-scale data. What We Offer
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.
- 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.
- 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.
- 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.
- Expert-level Python (pandas, NumPy, scikit-learn, async programming, API development with FastAPI). - Experience with vector databases and embeddings (Azure AI Search, Pinecone, Weaviate, Qdrant, FAISS, or pgvector). - Strong SQL skills and experience working with large-scale data.
- 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.
Benefits in the posting
Full benefits wording- Azure and AI certification sponsorship plus a continuous learning budget.
From the employer’s posting.
About Johnson Controls
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.
In the employer’s words · Read in context
Posting record
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- Live
- First seen by us
- Oct 15, 2026 · 14 days ago
- Recorded sightings
- 48
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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.
What we look for
Required
- professional experience in data science / ML, with building LLM or GenAI applications in production.
- Hands-on experience with agentic frameworks LangChain or LangGraph.
- Strong understanding of LLM application patterns including prompt engineering
- Expert-level Python (pandas, NumPy, scikit-learn, async programming, API development with FastAPI).
- Experience with vector databases and embeddings (Azure AI Search, Pinecone, Weaviate, Qdrant, FAISS, or pgvector).
- Strong SQL skills and experience working with large-scale data.
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.
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
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Lisbon-Lisbon-Portugal
- Access to cutting-edge GenAI tooling, compute, and cross-domain AI projects. - Flexible hybrid working model and collaborative culture. About Us
More source context
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
- Work authorization
- 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.
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