Expert AI Agentic Developer

Datamatics Technologies; Madrid; On-site; EUR 80,000 - 110,000; Full time

Job summary

Datamatics Technologies in Madrid seeks a senior scientist to lead the end-to-end delivery of agentic AI solutions. You will design and implement agent workflows, integrate with enterprise systems via APIs, and ensure governance, safety, and scalable adoption across use cases.

The role requires hands-on AI engineering, Python proficiency, and experience with cloud deployment, Kubernetes, and Snowflake data platforms.

Qualifications

• Curious, innovative team player with a can-do attitude and focus on delivering value to customers.
• Hands-on agentic AI experience, including designing and building agent workflows (planner-executor, tool calling, multi-agent, human-in-the-loop).
• Strong LLM ops and evaluation mindset: quality, latency, cost, and safety; ability to define test sets and run experiments.
• Guardrails and Responsible AI experience: input/output validation, prompt safety, data leakage prevention, and controls for regulated environments.
• Strong software engineering skills with Python; comfortable with notebook-based experimentation.
• Cloud and integration experience: deploying AI services in AWS, integrating via REST APIs; familiarity with containerisation/Kubernetes and CI/CD.
• Data/analytics platform experience (e.g., Snowflake) for grounding, retrieval, and context management; ability to translate stakeholder needs into solution requirements, KPIs, and adoption plans.

Responsibilities

• Own delivery from idea to production: frame business problems, shape AI solution designs, prototype quickly, and industrialize into production-ready services with measurable outcomes.
• Build agentic AI applications: design and implement agents that can reason, plan, use tools, and interact with enterprise systems (advisor tooling, analytics platforms, internal APIs).
• Partner with stakeholders end-to-end: collaborate with business leaders, architects, engineers, and control functions to ensure solutions deliver real value and can be adopted at scale.
• Engineer for governance and safety: implement evaluation strategies, guardrails, and human-in-the-loop patterns suitable for regulated environments (privacy, auditability, model risk).
• Enable reuse and scale: build reusable patterns, components, and reference implementations to accelerate delivery across a portfolio of use cases.
• Operate and improve: monitor agent behavior in production, iterate on prompts/tools/logic based on evals and feedback, and improve quality, cost, latency, and safety.

Skills

Agentic AI experience

LLM ops and evaluation mindset

Guardrails & safety

Python programming

Cloud & Kubernetes

Tools

Kubernetes

CI/CD

REST APIs

Snowflake

Job description

Main responsibilities in this role include, but are not limited to:

• Own delivery from idea to production: frame business problems, shape agentic Al solution designs, prototype quickly, and industrialize into production-ready services with measurable outcomes.
• Build agentic Al applications: design and implement agents that can reason, plan, use tools, and interact with enterprise systems (e.g., advisor tooling, analytics platforms, internal APls).
• Partner with stakeholders end-to-end: collaborate with Private Banking/AWM business leaders, architects, engineers, and control functions to ensure solutions deliver real value and can be adopted at scale
• Engineer for governance and safety: implement evaluation strategies, guardrails, and human-in-the-loop patterns suitable for regulated banking environments (privacy, auditability, model risk expectations).
• Enable reuse and scale: build reusable patterns, components, and reference implementations to accelerate delivery across a portfolio of use cases.
• Operate and improve: monitor agent behavior in production, iterate on prompts/tools/logic based on evals and feedback, and continuously improve quality, cost, latency, and safety.

Who you are

Collaboration. Ownership. Passion. Courage. These are the values that guide us in being at our best - and that we imagine you share with us. This is the right role for you if you are a curious, outcome-driven and pragmatic senior scientist who can take ownership, influence stakeholders, and raise modelling and engineering standards while delivering working solutions at pace.

Your background and skills include:

• Are a curious, innovative team player with a can-do attitude, always looking for ways on how we can unlock the next level for our customers.
• Hands-on agenticAl experience, including designing and building agent workflows (planner-executor, tool calling, multi-agent, human-in-the-loop).
• Strong LLM ops and evaluation mindset: quality/correctness, latency, cost, and safety, ability to define test sets and run disciplined experimentation.
• Guardrails and Responsible Al experience: input/output validation, prompt safety, data leakage prevention, and controls appropriate for regulated environments.
• Strong software engineering skills with Python (modular design, testing, version control) and comfort working in notebook-based experimentation.
• Cloud and integration experience: deploying Al services in AWS, integrating via REST APIs, and familiarity with containerisation/Kubernetes and CI/CD
• Data/analytics platform experience (eg., Snowflake) for grounding, retrieval, and context management. Business engineering strength: ability to translate stakeholder needs into solution requirements, KPIs, and adoption plans; st communication and collaboration skills.