Ejecutivo De Ventas – Tecnología Médica Robótica

Strattner Argentina; Victoria; Hybrid; ARS 1,800,000 - 3,000,000; Full time

Job summary

Boehringer Ingelheim S.A. is seeking an experienced Semantic Engineer to design, build, and operate an enterprise semantic foundation powering AI agents and knowledge-driven applications.

You will develop the Enterprise Semantic Layer, knowledge graphs, and MCP/agent tooling, ensuring security, governance, and scalable architectures across data domains. Hybrid, full-time role with collaboration across engineering, data and business stakeholders.

Qualifications

• 5+ years of software engineering or AI platform development.
• Strong Python and modern API frameworks.
• Hands-on with RDF, OWL, SPARQL, SHACL.
• Experience with knowledge graphs or semantic layers.
• Understanding of Git workflows, CI/CD, and cloud-native architectures.
• Strong communication with data engineers, architects, AI engineers and stakeholders.

Responsibilities

• Design and evolve the Enterprise Semantic Layer for AI agents and analytics.
• Build knowledge graphs, ontologies, and semantic models for enterprise data.
• Develop MCP servers, semantic tools, and agent-facing services.
• Define testing, monitoring, and governance for semantic AI systems.

Skills

Python

Backend dev

Knowledge graphs

API development

CI/CD

Git workflows

Tools

RDF/OWL

SPARQL

SHACL

Job description

Semantic Engineer

Hoy

The Position
We are seeking an experienced AI Semantic Architect to design, build, and operate the semantic foundation that powers enterprise‑scale AI, intelligent agents, and knowledge‑driven applications.
This role is focused on the development of the Enterprise Semantic Layer, providing a unified and governed representation of enterprise knowledge across data domains, systems, and applications. Leveraging knowledge graphs, ontologies, semantic models, metadata systems, and retrieval technologies, you will build the technical capabilities that enable AI systems to discover, retrieve, reason over, and act upon enterprise knowledge.
Unlike ontology governance or data modeling roles, this position is focused on engineering reusable platform components such as semantic services, GraphRAG architectures, MCP servers, retrieval pipelines, and agent tooling that accelerate delivery of Enterprise Brain capabilities.

Tasks and responsibilities

Semantic Layer Engineering

• Design, implement, and evolve the Enterprise Semantic Layer that abstracts enterprise knowledge and makes it consumable by AI agents, applications, and analytical platforms.
• Translate heterogeneous enterprise data sources into a unified semantic representation using knowledge graphs, ontologies, semantic models, metadata, and business context.
• Design scalable architectures enabling interoperability across data domains through shared semantics and common business vocabularies.
• Ensure enterprise‑grade security, governance, scalability, observability, and maintainability of semantic platform components.

Semantic Layer & KG Development

• Design and implement knowledge graph and semantic layer architectures using RDF, OWL, SHACL, SKOS, semantic models, and graph technologies.
• Develop retrieval solutions leveraging knowledge graphs, ontologies, embeddings, metadata, and semantic search capabilities.
• Support integration of enterprise knowledge graphs with platforms such as Snowflake, Databricks, Neo4j, vector databases, search engines, and AI platforms.

Agent & MCP Engineering

• Design and implement MCP servers, semantic tools, and reusable agent‑facing services.
• Develop typed tool definitions and YAML/JSON‑based tool specifications for enterprise agents.
• Build reusable frameworks and accelerators for Agentic AI solutions.
• Define testing, evaluation, monitoring, and governance approaches for semantic AI and agentic systems.

Required

• 5+ years of experience in software engineering, backend engineering, data platforms, or AI platform development.
• Strong proficiency in Python and modern API development frameworks.
• Hands‑on experience with semantic web technologies including RDF, OWL, SPARQL, and SHACL.
• Experience implementing and operating knowledge graph or semantic layer technologies.
• Strong understanding of software engineering best practices, Git workflows, CI/CD, testing, and cloud‑native architectures.
• Ability to communicate effectively with data engineers, architects, AI engineers, and business stakeholders

Desirable

• Experience with metaphactory, Stardog.
• Experience with Snowflake Semantic Models and Open Semantic Interoperability (OSI) compliant YAML specifications.
• Experience implementing MCP servers and agent platforms.
• Experience working in regulated environments such as pharmaceutical, healthcare, or life sciences industries.

JOB ID
37785

Job function
Information technology

Career level
Experienced professionals

Organization
Boehringer Ingelheim S.A.

Working time
Full‑Time

Job flexibility
Hybrid

Boehringer Ingelheim is an equal opportunity global employer who takes pride in maintaining a diverse and inclusive culture. We embrace diversity of perspectives and strive for an inclusive environment, which benefits our employees, patients, and communities. All qualified applicants will receive consideration for employment without regard to a person's actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law