Lead Data Scientist

Posted 3 Hours Ago
Be an Early Applicant
Hiring Remotely in Barcelona, Cataluña, ESP
Remote or Hybrid
Senior level
Artificial Intelligence • Big Data • Cloud • Information Technology • Software • Big Data Analytics • Automation
Dynatrace delivers answers and intelligent automation from data.
The Role
The Lead Data Scientist will design and build generative AI capabilities using LLMs, overseeing the architecture, mentoring staff, and ensuring production readiness of the systems.
Summary Generated by Built In
Your role at Dynatrace

Dynatrace makes it easy and simple to monitor and run the most complex, hyper-scale multicloud
systems. Dynatrace is a full stack and completely automated monitoring solution that can trackevery user, every transaction, across every application.

Our team is looking for a Lead Data Scientist specialized in Large Language Models (LLMs) to design, build, and scale generative AI capabilities for real-world, enterprise-grade use cases. In this hands-on technical leadership role, you’ll own the end-to-end LLM stack, from data/knowledge, Ingestion and retrieval to prompt and tool-use architecture, evaluation frameworks,safety/guardrails, and cost/latency optimization.

Your Tasks
• Own the LLM system architecture: Retrieval pipelines, prompt/tool design,
routing/fallbacks, safety layers, and telemetry, optimized for quality, latency, and cost.
• Establish technical standards for RAG: content ingestion, chunking/windowing, hybrid
retrieval, reranking, query understanding, and structured output contracts.
• Define evaluation strategy: Create a rigorous eval suite covering answer correctness,
attribution/grounding, toxicity/safety, privacy leakage, determinism, latency, and cost.
• Formalize LLMOps: Versioning for prompts/datasets/models, experiment governance,
prompt and dataset registries, and promotion criteria from dev - staging - prod.
• Drive tool/agent design: API schema design for function calling, error handling, recovery
strategies, self-correction, and guardrail integration.
• Make build-vs-buy calls: Weigh managed providers vs. open-source/self-hosted,
considering performance, cost, IP, privacy, and compliance.
• Mentoring: Provide deep technical mentorship on prompting, retrieval design, evals, and
safe deployment; lead reviews of prompts, pipelines, and evaluation reports.


Hands-on Data Science

• Implement end-to-end RAG systems: ingestion - chunking - embeddings - hybrid search -
rerank - prompt assembly - tool calls - post-processing.
• Engineer robust prompts/tools: reusable templates, multi-turn strategies, structured
outputs via JSON Schema/Pydantic.

• Select/tune models: foundation models, embeddings, rerankers; apply LoRA/PEFT or
distillation when justified.
• Build eval corpora: golden sets, KPIs for accuracy, groundedness, deflection, tool
success.
• Implement guardrails: PII/PHI detection, policy prompts, jailbreak resistance, filters,
safety scorecards.
• Productionize: ship resilient services with analytics, alerts (drift, quality, cost), SLOs, etc.
• Optimize for scale: token, latency, cost; caching, context packing, batching, speculative
decoding, routing by intent

What will help you succeed

Minimum requirements:
• Advanced CS/AI/ML degree or equivalent, strong ML background.
• 7+ years DS/ML, 3+ years NLP /LLMs, shipped production systems.
• Python and core ML stack: 5+ years of professional Python.
• Data engineering for unstructured data (3+ years): text processing, parsing, embedding-
friendly preprocessing.
• Proven RAG expertise (1+ years): embeddings, retrieval, reranking, chunking.
• Evaluation depth (1+ years): offline/online evals for accuracy, grounding, safety.
• Safety/privacy (1+ years): moderation, PII/PHI redaction, policy enforcement.
• LLMOps (1+ years): prompt/version management, experiment tracking, monitoring.
• Excellent communication: explain trade-offs, drive data decisions.

Desirable experiance:
• Serving/scaling: vLLM/TGI, Ray Serve, Triton; GPU/CPU trade-offs.
• Tuning/distillation: LoRA/PEFT, safety alignment, synthetic data.
• Domain: observability, support systems, multilingual, regulated environments.
• Cloud/security: Snowflake/AWS, managed vs self-hosted.
• Experience with graph-based knowledge bases (e.g., GraphDB, Neo4j) and knowledge
graphs to complement RAG systems with entity modeling and relationship-aware retrieval.

Why you will love being a Dynatracer

• Working models that offer you the flexibility you need, ranging from full remote options to
hybrid ones combining home and in-office work
• A team that thinks outside the box, welcomes unconventional ideas, and pushes
boundaries
• An environment that fosters innovation enables creative collaboration and allows you to
grow
• A globally unique and tailor-made career development program recognizing your
potential, promoting your strengths, and supporting you in achieving your career goals
• A truly international mindset with Dynatracers from different countries and cultures all
over the world, and English as the corporate language that connects us all
• A culture that is being shaped by our global team’s diverse personalities, expertise, and
backgrounds
• A relocation team that is eager to help you start your journey to a new country, always
there to support and by your side. If you need to relocate for a position you’re applying for,
we offer you a relocation allowance and support with your visa, work permit,accommodation .

Top Skills

AWS
Graphdb
Llms
Ml
Neo4J
Nlp
Python
Rag
Snowflake

What the Team is Saying

Michael Polter
Jamie Mallett
Trevor Ealy
Hannah Fleming
Kristen Hanlan
Am I A Good Fit?
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The Company
HQ: Boston, MA
5,200 Employees
Year Founded: 2005

What We Do

Dynatrace lets customers understand their business like never before, so they can see beyond the complexity, find and fix problems faster and automate manual tasks with Al — so they can focus on what truly matters: running their business.

Why Work With Us

In a world that runs on software, our Al-driven insights cut through the noise, allowing you to focus on what truly matters by automating manual tasks and resolving issues with pinpoint accuracy. Our culture, fueled by curiosity, openness, and authenticity, drives our pursuit of innovation and excellence in crafting the Dynatrace platform.

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Dynatrace Teams

Dynatrace Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Majority of roles are hybrid with flexibility. Please speak with our recruiting team for specific details on hybrid work.

Typical time on-site: 2 days a week
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