Software Engineer contributing to design, development, deployment, and support of enterprise-grade applications and data solutions.
Responsibilities
Design, develop, test, and maintain scalable data-driven applications, APIs, and integration solutions using modern software engineering practices.
Build and support applications utilizing relational, NoSQL, and graph databases while ensuring high performance, reliability, and scalability.
Develop and deploy cloud-based solutions using platforms such as Azure and AWS, implementing containerization and distributed builds.
Collaborate with multi-functional teams to develop and implement Generative AI, Agent, and AI-Enabled applications applying concepts such as RAG and Agentic AI solutions.
Participate in software lifecycle activities including version control, code reviews, deployment automation, troubleshooting, and continuous improvement.
Requirements
Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or a related technical field.
Nice to have: Generative AI
Nice to have: Large Language Models (LLMs)
Nice to have: Retrieval-Augmented Generation (RAG)
Software Engineer contributing to design, development, deployment, and support of enterprise-grade applications and data solutions.
Responsibilities
Design, develop, test, and maintain scalable data-driven applications, APIs, and integration solutions using modern software engineering practices.
Build and support applications utilizing relational, NoSQL, and graph databases while ensuring high performance, reliability, and scalability.
Develop and deploy cloud-based solutions using platforms such as Azure and AWS, implementing containerization and distributed builds.
Collaborate with multi-functional teams to develop and implement Generative AI, Agent, and AI-Enabled applications applying concepts such as RAG and Agentic AI solutions.
Participate in software lifecycle activities including version control, code reviews, deployment automation, troubleshooting, and continuous improvement.
Requirements
Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or a related technical field.
Nice to have: Generative AI
Nice to have: Large Language Models (LLMs)
Nice to have: Retrieval-Augmented Generation (RAG)
Shape how platforms are designed and built, setting clear architecture direction to improve reliability, speed, and long-term maintainability in financial services.
Compensation
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.
Responsibilities
Define target and transitional architectures and set practical guardrails for resiliency across application, data, and integration layers
Lead solution design from concept to production, creating ADRs, HLDs, and LLDs that align to enterprise reference architectures and controls
Run or contribute to design councils, perform architecture/design reviews, and manage exceptions and technical risk with clear remediation plans
Guide implementation details (service boundaries, API contracts, data models, error handling, idempotency, failure modes, back-pressure)
Ensure designs include HA/DR, observability (logs/metrics/traces), and capacity/performance considerations, and are ready for chaos and DR testing
Requirements
Formal training or certification on software engineering concepts
Nice to have: AI/ML for operations automation
Nice to have: Anomaly/outlier detection
Nice to have: Predictive capacity
Nice to have: Root-cause hints
I
Senior Data Scientist - Ontology & Semantic Modeling
Design the foundational knowledge layer for enterprise AI and analytics initiatives using formal ontologies and semantic modeling.
Responsibilities
Design, develop, and maintain formal domain ontologies, taxonomies, and semantic schemas (OWL, RDF, RDFS, SHACL).
Translate complex business rules, domain concepts, and entity relationships into structured semantic models.
Collaborate closely with Knowledge Graph Engineers and Agentic AI Engineers to ground LLM workflows and GraphRAG pipelines in trusted enterprise context.
Establish ontology governance, versioning standards, and validation rules across cross-functional data sources.
Align enterprise semantic layers with analytical platforms (Databricks) and operational CRM ecosystems.
Lead a significant knowledge engineering scope and function within a large program; actively contribute to thought leadership. Shape how a substantial body of work formulates real-world problems into scalable AI and KG solutions, and set the technical direction for that scope.
Responsibilities
Leads the build of Knowledge Graph solutions that transform a client's data architecture within program scope
Directs the design, development, and implementation of AI and semantic solutions
Works with project leaders, delivery leads, and client stakeholders to create stand-out, graph-powered Data & AI offerings
Develops strong client relationships and earns the trust of key advisors
Makes the business case for the semantic layer solution recommended to the client
The Semantic Engineer is responsible for leading, designing, developing, and maintaining our enterprise-level semantic hub. This platform serves as the foundational data layer bridging the gap between vast enterprise knowledge and advanced AI systems.
Compensation
Salary range 14,100 - 26,300 PLN gross based on the employment contract. The expected salary range for this position, based on the primary location of Warsaw Grafit is 170,100.00 PLN - 315,900.00 PLN. In addition to base pay, this role may be eligible for a discretionary annual bonus with a target of 15% subject to both individual and company performance.
Responsibilities
Leads the design, build, and maintenance of scalable data pipelines and graph architectures.
Independently drives data integration projects from ingestion to semantic transformation, establishing unified enterprise ontologies.
Solves complex data modeling, ingestion, and querying challenges.
Evaluates, benchmarks, and optimizes the performance of data access tools to ensure AI systems fetch enterprise context efficiently, accurately, and with minimal latency.
Collaborates directly with data owners, domain experts, and AI application teams to thoroughly understand business requirements.
Support the advancement of the Sponsor's solution with highly technical software development to meet complex and evolving mission needs, focusing on data correlation, aggregation, and graphing.
Compensation
Virginia Pay Range
$150,000 - $250,000
Pay Range: At GRVTY, we understand that compensation is influenced by many factors—such as geographic location, federal contract labor categories, wage rates, prior experience, skillsets, education, and certifications.
We’re proud to offer a work environment that empowers our team to achieve a strong work-life balance. GRVTY provides competitive pay, comprehensive benefits, and meaningful opportunities for professional growth.
Virginia Pay Range
$150,000—$250,000 USD
Responsibilities
Design and operate big data systems
Develop and operate graph traversal capabilities
Develop and operate NoSQL solutions to complex big data applications
Design and operate large-scale serverless geospatial indexes
Build and operate high-performance data processing pipelines
The Semantic Engineer is responsible for leading, designing, developing, and maintaining our enterprise-level semantic hub. This platform serves as the foundational data layer bridging the gap between vast enterprise knowledge and advanced AI systems.
Compensation
Salary range 14,100 - 26,300 PLN gross based on the employment contract. The expected salary range for this position, based on the primary location of Warsaw Grafit is 170,100.00 PLN - 315,900.00 PLN. In addition to base pay, this role may be eligible for a discretionary annual bonus with a target of 15% subject to both individual and company performance.
Responsibilities
Leads the design, build, and maintenance of scalable data pipelines and graph architectures.
Independently drives data integration projects from ingestion to semantic transformation, establishing unified enterprise ontologies.
Solves complex data modeling, ingestion, and querying challenges.
Evaluates, benchmarks, and optimizes the performance of data access tools to ensure AI systems fetch enterprise context efficiently, accurately, and with minimal latency.
Collaborates directly with data owners, domain experts, and AI application teams to thoroughly understand business requirements.
New College Grad - Software EngineerNewMicron Technology · Boise, US
Senior Lead Architect-Enterprise ArchitectureNewJPMC Candidate Experience page · Jersey City, US
Senior Data Engineer – Knowledge GraphNewElevus · Lisbon, Portugal
Semantic Engineer - RDT Data PlatformsNewRoche · Warsaw, Poland
AI Backend DeveloperNewSopra Steria · Germany
Software Developer (Systems Software)NewGRVTY · Chantilly, US