Enterprise Knowledge Graph Developer

ERNI; Mandaluyong; Hybrid; PHP 1,800,000 - 3,000,000; Full time

Benefits offered by this job

Career Stability

Private HMO and insurance from day one

Jubilee trip to European ERNI sites

13th-month pay and comprehensive govt.

Skill Enhancement: free training and认证

Baby Basket

Fruit Basket

Office snacks and coffee

Job summary

ERNI, founded in 1994 and headquartered in Switzerland, operates a growing APAC hub in Mandaluyong. We seek a Senior Enterprise Knowledge Graph Developer to design, build, and scale a unified semantic data layer enabling GenAI-powered insights for global clients.

You will model ontologies, construct graph ETL pipelines, manage distributed graph databases, and integrate LLM-driven workflows, collaborating with cross-functional teams across Europe, APAC, and the USA.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Knowledge Engineering, or a highly technical equivalent field.
• 4–6 years in core data engineering or software development with 2–3 years on production-grade graph databases and semantic web stacks.

Responsibilities

• Ontological Modeling & Schema Design for scalable enterprise ontologies and taxonomies.
• Translate complex business rules into semantic models using OWL/RDF/SHACL.
• Ensure modular semantic models across multi-departmental units.
• Graph Pipeline Infrastructure & Integration (Graph ETL) to ingest and map data into the knowledge graph.
• Incorporate entity resolution and disambiguation across systems.
• Graph Database Management & Optimization for fast queries and sub-second responses.
• GenAI, LLM, and Agentic AI Enablement with GraphRAG and API exposure.

Skills

Semantic web standards

Graph databases

Backend development

Python

Java/Scala

Spark

Kafka

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Knowledge Engineering

Tools

Neo4j

Memgraph

Stardog

GraphDB

Neptune

Docker

Apache Spark

Apache Kafka

Job description

Job Description:

Founded in 1994 and headquartered in Switzerland, ERNI is a leading Software Development company with over 800 employees worldwide. Specializing in IT and software engineering, we drive innovation in process and technology. Our first service center in Asia Pacific, located in Metro Manila (Mandaluyong), supports clients across Europe, APAC, the Philippines, and the USA. As we continue to grow, were looking for passionate and motivated individuals to join our team.

Why ERNI is the Perfect Place for You:

• International Exposure: Work with global clients on cutting-edge projects.
• Inclusive Culture: Thrive in a collaborative and diverse work environment.
• Career Development: Enjoy continuous learning and professional growth opportunities.

Perks and Benefits:

• Career Stability: Enjoy a stable career path with ample project opportunities.
• Immediate Coverage: Private HMO and insurance benefits from day one.
• Jubilee Celebration: A 5-year milestone includes a complimentary trip to any European ERNI sites.
• Comprehensive Benefits: Government-mandated benefits including 13th-month pay.
• Skill Enhancement: Access free training and certifications.
• Baby Basket: To welcome your newborn to the ERNI family.
• Fruit Basket: Boost of vitamins during hospitalization.
• Office Perks: Enjoy free snacks and coffee.

Growth and Opportunities:

• Free Training: Advance your skills through technical and non-technical training.
• Challenging Projects: Engage in complex software projects across MedTech, Industry, Finance, and Transportation.
• Supportive Environment: Benefit from a team dedicated to guiding and supporting yoursuccess.
• Recognition and Advancement: Receive acknowledgment for your efforts and opportunities for promotion.
• Open Communication: Experience transparency and value your input in our culture.

Flexibility:

• Hybrid Work Setup: Balance remote and in-person work for better work-life integration.

Events:

• Connect and Celebrate: Participate in a variety of events including leisure, summer, family, social, and year-end gatherings.

What are our wishes:

TECHNICAL SKILLS PROFILE

Core Technologies

• RDF/OWL/SHACL | SPARQL / Cypher | Neo4j / Amazon Neptune | Stardog / GraphDB | Python (rdflib, NetworkX) | Java / Scala | Apache Spark / Kafka | GraphRAG / LangChain | Entity Resolution | CI/CD & Docker

Required Minimum Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Knowledge Engineering, or a highly technical equivalent field.
• Experience: Minimum of 4-6 years in core data engineering or software development, with at least 2-3 years of dedicated hands‑on experience designing and operating production‑grade graph databases and semantic web stacks.

Preferred Technical Competencies

• Deep literacy in W3C semantic web standards (RDF, RDFS, OWL, SPARQL, SHACL).
• Proven mastery over either Property Graph systems (Neo4j, Memgraph) or RDF Triplestores/Quadstores (Stardog, GraphDB, Ontotext, AWS Neptune).
• Proficiency in backend development using Python or Java/Scala, alongside enterprise pipeline frameworks like Apache Spark, Apache Kafka, or NiFi.
• Direct exposure to building semantic contexts for LLMs, knowledge distillation, or vector-graph hybrid index stores.

KEY COMPETENCIES & SOFT SKILLS

• Abstract & Systems Thinking: Ability to step back from tabular flat file systems and naturally conceptualize multi-dimensional data networks, hyper-graphs, and structural relationships.
• Cross-Functional Translation: Exceptional capacity to talk to non-technical business leaders to distill ambiguous operational terminology into structured, definitive business glossaries and taxonomies.
• Rigorous Data Governance Mindset: A firm commitment to programmatic data quality validation, automated contract verification, and enforcing strictly typed data schemas at ingestion borders.

How can you contribute to the team?

ROLE OVERVIEW

The Enterprise Knowledge Graph Developer is a specialized data engineering and architecture role responsible for designing, building, and scaling the organization’s unified semantic data layer. This position bridges the gap between disparate enterprise data silos, relational systems, and downstream intelligent applications (including GenAI, LLM agents, and semantic search engine platforms) by structuring organizational data into a high-performance, interconnected graph network.

POSITION METADATA

• Job Level: Senior / Lead Specialist
• Department: Enterprise Data & AI Architecture
• Reports To: Director of Data Engineering / Principal Architect
• Core Focus: Ontology Design, Graph ETL, Semantic Linking

CORE RESPONSIBILITIES

• Ontological Modeling & Schema Design

1. Collaborate with domain experts, business analysts, and data stewards to conceptualize, define, and build scalable enterprise ontologies and taxonomies.
2. Translate complex business rules and relationship constraints into formal semantic models using W3C standards (OWL, RDF, SHACL, SKOS)
3. Ensure semantic models remain highly modular, extensible, and integrated across multi-departmental business units.

• Graph Pipeline Infrastructure & Integration (Graph ETL)

1. Design, implement, and maintain scalable data pipelines (batch and real-time) to ingest, extract, transform, and map structured, semi-structured, and unstructured data into the centralized knowledge graph.
2. Incorporate Entity Resolution, Record Linkage, and disambiguation algorithms to dynamically reconcile duplicate identities across disparate transactional systems.
3. Construct robust mappings from relational DBs, data lakes, and document stores using declarative mapping languages (e.g., R2RML, RML).

• Graph Database Management & Optimization

1. Administer, tune, and maintain distributed native graph databases (GraphDB, Neo4j, Neptune, AnzoGraph, or Stardog).
2. Write, test, and perform fine‑grained optimization of complex, multi‑hop semantic queries using SPARQL, Cypher, or Gremlin.
3. Implement partitioning, sharding, caching, and index strategies to guarantee sub‑second query execution for real‑time upstream enterprise systems.

• GenAI, LLM, and Agentic AI Enablement

1. Integrate the Enterprise Knowledge Graph with Large Language Model (LLM) frameworks to implement high‑precision Graph Retrieval‑Augmented Generation (GraphRAG).
2. Expose semantic layers via secure GraphQL or RESTful APIs to feed multi‑agent autonomous frameworks, ensuring deterministic and highly contextual reasoning paths.
3. Utilize graph analytics, embeddings, and Graph Neural Networks (GNNs) to drive advanced inferencing and recommendation capabilities.

Requirements: