Principal System Engineer (Buenos Aires, Argentina, Capital Federal)
About this opportunity
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 details
How this role compares
Computed from every other active Information Technology role in our database, not just this employer's listings.
We currently track 569 comparable Principal Information Technology roles across 55 biopharma companies.
Salary context
72 of 569 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 569 comparable roles
+ 26 more countries
Seniority mix
569 of 569 peers have a known seniority level
Therapeutic area mix
5 of 569 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
Notify me about similar jobs
Get an email when we spot other openings like this one – same job function, comparable seniority, roles you'd actually want to see.
Or follow a whole field: get every new Information Technology job in Argentina, and choose locations and companies.
How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.