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Contract Knowledge Graph Software Engineer Jobs in Massachusetts

NAVA Software is looking for an AI Engineer Details: AI Engineer Location: 100% Remote Duration: 6+ ... Knowledge graph implementation (Neo4j preferred). LLM optimization & improved response handling.

... Graph. As a Principal Software Engineer, you will work across application code and infrastructure ... bar through knowledge sharing and best practices. What You'll Bring: * At least 5 years of ...

Principal Software Engineer

Boston, MA · On-site

$152K - $228K/yr

... bar through knowledge sharing and best practices. What You'll Bring: * At least 5 years of ... Familiarity with data lake storage frameworks such as Delta Lake and graph databases such as AWS ...

Proficiency in algorithm design, software development, and mathematical modeling with programming ... Strong knowledge of path planning techniques, such as graph-based search (A*, D* Lite), sampling ...

Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a ... Define multi-tenant schemas and Knowledge Graph ontologies that allow LLM agents to perform complex ...

Proficiency in algorithm design, software development, and mathematical modeling with programming ... Strong knowledge of path planning techniques, such as graph-based search (A*, D* Lite), sampling ...

Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a ... Define multi-tenant schemas and Knowledge Graph ontologies that allow LLM agents to perform complex ...

GNC Senior Software Engineer

Waltham, MA

$132K - $174K/yr

Proficiency in algorithm design, software development, and mathematical modeling with programming ... Strong knowledge of path planning techniques, such as graph-based search (A*, D* Lite), sampling ...

GNC Senior Software Engineer

Waltham, MA

$132K - $174K/yr

Proficiency in algorithm design, software development, and mathematical modeling with programming ... Strong knowledge of path planning techniques, such as graph-based search (A*, D* Lite), sampling ...

GNC Senior Software Engineer

Waltham, MA · On-site

$132K - $174K/yr

Proficiency in algorithm design, software development, and mathematical modeling with programming ... Strong knowledge of path planning techniques, such as graph-based search (A*, D* Lite), sampling ...

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Contract Knowledge Graph Software Engineer information

How does a Contract Knowledge Graph Software Engineer typically collaborate with data scientists and domain experts during a project?

As a Contract Knowledge Graph Software Engineer, you’ll often work closely with data scientists and domain experts to ensure that the knowledge graph accurately represents the underlying data and business logic. Collaboration usually involves regular meetings to clarify requirements, discuss data models, and review results. You may be tasked with translating complex domain concepts into graph structures, while also providing feedback on data quality and integration challenges. This cross-functional teamwork ensures that the final product meets both technical standards and business needs.

What is the difference between Contract Knowledge Graph Software Engineer vs Contract Data Engineer?

AspectContract Knowledge Graph Software EngineerContract Data Engineer
Required CredentialsBachelor's in CS or related, knowledge of graph databases, programming skillsBachelor's in CS, experience with data pipelines, SQL, and cloud platforms
Work EnvironmentTech companies, consulting firms, project-based rolesData-focused teams, cloud environments, analytics projects
Industry UsageAI, semantic web, knowledge managementData warehousing, big data, analytics

The Contract Knowledge Graph Software Engineer primarily focuses on developing and maintaining knowledge graphs using graph databases and semantic technologies, while the Contract Data Engineer concentrates on building data pipelines, managing large datasets, and supporting analytics. Both roles require strong programming skills and are often found in tech-driven industries, but they serve different core functions within data and knowledge management ecosystems.

What is a Contract Knowledge Graph Software Engineer?

A Contract Knowledge Graph Software Engineer is a professional who specializes in designing, developing, and maintaining knowledge graphs on a contract basis. Knowledge graphs are data structures that represent relationships between entities, enabling more effective data integration and semantic search. These engineers often work with graph databases, semantic web technologies, and ontologies to help organizations manage and leverage complex data. Their contract role means they are typically hired for specific projects or fixed periods rather than as permanent employees.

What are the key skills and qualifications needed to thrive as a Contract Knowledge Graph Software Engineer, and why are they important?

To thrive as a Contract Knowledge Graph Software Engineer, you need a strong background in computer science, proficiency in graph databases (such as Neo4j or Amazon Neptune), and experience with knowledge representation and data modeling. Familiarity with programming languages like Python or Java, as well as tools for semantic web technologies (RDF, SPARQL), is typically required. Strong problem-solving skills, adaptability, and effective collaboration are essential soft skills in this role. These competencies ensure efficient design and implementation of complex knowledge graphs, enabling organizations to unlock valuable insights from their data.
What are the most commonly searched types of Knowledge Graph Software Engineer jobs in Massachusetts? The most popular types of Knowledge Graph Software Engineer jobs in Massachusetts are:
What cities in Massachusetts are hiring for Contract Knowledge Graph Software Engineer jobs? Cities in Massachusetts with the most Contract Knowledge Graph Software Engineer job openings:

Director, Knowledge Graph & Semantics - HYBRID ROLE

Vrtx

Boston, MA • Hybrid

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 days ago


Job description

Job Description

This is a Hybrid position requiring 3 days a week in our Boston office

We are seeking an experienced engineering leader to build and operate Vertex's enterprise Knowledge Graph and Semantic Layer: the unified, navigable representation of Vertex's data, concepts, and relationships that AI agents and analytical systems traverse to reason over our business. Vertex Pharmaceuticals is in a transformational period, and the AI team is at the center of our AI-first strategy, delivering AI solutions that empower executives, researchers, and business users to make faster, more confident decisions.

As part of the Vertex Data Engineering team, you will lead the Knowledge Graph & Semantics function within Knowledge & Grounding. Your team builds the graph that connects Vertex across clinical, research, regulatory, and commercial domains, and the AI semantic layer that defines the business meaning, metrics, and dimensions that sit on top of it. The capability you build becomes the substrate that AI agents traverse to ground their reasoning, and that analytical systems use to answer cross-domain questions consistently across the enterprise.

As the Director of Knowledge Graph & Semantics, you will define the graph and semantic strategy for Vertex, select the underlying technology stack, and lead the engineering team that brings it to life.

The capability you build will accelerate every downstream AI and analytics initiative at Vertex by giving them a single, governed, traversable model of how Vertex's data fits together.

Key Duties and Responsibilities:

  • Enterprise Knowledge Graph. Design, build, and operate Vertex's enterprise knowledge graph spanning clinical, research, regulatory, and commercial domains, including ingestion, storage, query, and lifecycle management of nodes, edges, and properties.

  • Semantic Layer. Build and govern the enterprise semantic layer that enables metrics, dimensions, business entities, and relationships in a single, consistent model used by AI agents.

  • Graph and Semantic Strategy. Define Vertex's strategy for graph and semantic platform, including technology selection (graph database, AI semantic layer tooling, query API) and the architecture that unifies them.

  • Ontology Partnership. Partner with the ontology and data modeling function to translate domain ontologies into the graph, ensuring fidelity to source models and consistency across domains.

  • Agent Traversal & Retrieval. Build the graph traversal and retrieval interfaces that AI agents and other consumers use to ground their reasoning, including pattern queries, semantic search over graph context, and graph-aware retrieval for RAG systems.

  • Application & System Onboarding. Partner with application and system owners across Vertex to onboard their systems into the enterprise knowledge graph and semantic layer.

  • Production Operations. Own SLAs, observability, query performance, cost, and continuous improvement for the graph and semantic layer in production.

Knowledge and Skills:

  • Proven Experience. 10+ years of experience in data engineering, AI/ML, or advanced analytics, with 3+ years specifically focused on knowledge graphs, semantic technologies, or enterprise data modeling at scale.

  • Knowledge Graph Expertise. Deep hands-on experience designing and operating enterprise knowledge graphs, including schema design, ingestion, query, and traversal patterns. Familiarity with multiple graph paradigms (property graph, RDF/semantic web, hybrid graph + vector approaches) and the trade-offs between them.

  • Semantic Layer Expertise. Strong experience building and governing semantic layers (e.g., dbt Semantic Layer, Cube, AtScale, LookML, or comparable) that serve analytics and AI consumers consistently.

  • Cloud Data Platforms. Strong experience with Snowflake and/or Databricks in enterprise environments, including how graph and semantic capabilities integrate with these platforms.

  • Cross-Domain Data Integration. Track record of integrating data across multiple business domains, including entity resolution, master data, and lineage at enterprise scale.

  • AI & Agent Grounding. Working understanding of how knowledge graphs and semantic layers are consumed by AI agents and RAG systems, including graph-aware retrieval and traversal for agent reasoning.

  • Production Operations. Track record of operating graph and analytical systems in production with high availability, query performance, and continuous improvement.

  • Leadership & Communication. Proven ability to lead technical teams, communicate with executive stakeholders, and translate business needs into graph and semantic models.

Preferred

  • Pharma or Life Sciences Context. Experience in pharmaceutical, biotech, or life sciences data environments. Familiarity with clinical, regulatory, and commercial data domains is a plus.

  • Regulated Environment Experience. Working knowledge of GxP, 21 CFR Part 11, and validated-system constraints on data and AI deployments.

  • Life Sciences Ontologies. Familiarity with industry ontologies and standards (e.g., SNOMED CT, MedDRA, LOINC, RxNorm, CDISC, IDMP) and how they map into enterprise graph models.

  • Graph Query Languages. Hands-on experience with Cypher, SPARQL, Gremlin, GQL, or comparable graph query languages.

  • LLM Integration with Graphs. Experience with text-to-Cypher, text-to-SPARQL, or other LLM-driven graph query generation, and graph-augmented retrieval for AI systems.

    Pay Range:

    $216,400 - $324,600

    Disclosure Statement:

    The range provided is based on what we believe is a reasonable estimate for the base salary pay range for this job at the time of posting. This role is eligible for an annual bonus and annual equity awards. Some roles may also be eligible for overtime pay, in accordance with federal and state requirements. Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.

    At Vertex, our Total Rewards offerings also include inclusive market-leading benefits to meet our employees wherever they are in their career, financial, family and wellbeing journey while providing flexibility and resources to support their growth and aspirations. From medical, dental and vision benefits to generous paid time off (including a week-long company shutdown in the Summer and the Winter), educational assistance programs including student loan repayment, a generous commuting subsidy, matching charitable donations, 401(k) and so much more.

    Flex Designation:

    Remote-Eligible

    Flex Eligibility Status:

    In this Remote-Eligible role, you can choose to be designated as:
    1. Remote: work remotely five days per week and come into the office on occasion - you're always welcome on-site; or select
    2. Hybrid: work remotely up to two days per week; or select
    3. On-Site: work five days per week on-site with ad hoc flexibility.

    Note: The Flex status for this position is subject to Vertex's Policy on Flex @ Vertex Program and may be changed at any time.

    #LI-Remote

    Company Information

    Vertex is a global biotechnology company that invests in scientific innovation.

    Vertex is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, sexual orientation, marital status, or any characteristic protected under applicable law. Vertex is an E-Verify Employer in the United States. Vertex will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

    Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should make a request to the recruiter or hiring manager, or contact Talent Acquisition at ApplicationAssistance@vrtx.com