1 day ago
Remote, GermanyMid Level
Base Salary
$250k - $300k/yr
Responsibilities
- Own the technical customer relationship across discovery, design, pilot, production, and expansion.
- Run customer discovery and qualify AI use cases against business outcomes.
- Design Arango multimodel architectures, graph data models, AQL queries and traversals, and GraphRAG retrieval systems.
- Define success criteria, service objectives, data governance requirements, and phased delivery plans.
- Build reference implementations and prototypes involving graph schemas, data connectors, GraphRAG pipelines, APIs, and agent orchestration.
- Guide secure, observable production deployments with CI/CD, infrastructure-as-code, and testing.
- Architect graph, vector, and hybrid retrieval using chunking, embeddings, ranking, caching, and evaluation practices.
- Design ETL/ELT pipelines, vector indexes, graph ingestion, metadata governance, monitoring, alerting, and dashboards.
- Design access control, secrets management, audit logging, PII redaction, and content safety controls.
- Produce architecture documentation and runbooks, train customer teams, and provide reusable delivery patterns.
- Represent customer feedback to Arango product and engineering teams to influence the roadmap.
Requirements
- Deep expertise in graph data modeling, graph queries and traversals, graph algorithms, and knowledge-graph design for AI.
- Direct experience building GraphRAG or knowledge-graph-backed retrieval for LLM applications.
- At least 3 years of experience in software engineering, solution architecture, or technical professional services, including production systems.
- Strong applied AI and Python skills, with knowledge of data structures, systems design, concurrency, and networking.
- Strong database experience across graph, NoSQL, key-value, and document models.
- Hands-on experience with modern LLMs, LLM tooling, retrieval and vector databases, and hybrid graph-vector retrieval.
- Experience with cloud platforms, containers, infrastructure-as-code, CI/CD, observability, and performance tuning.
- Excellent customer-facing communication skills across executive, architecture, and engineering audiences.
- Preferred qualifications include ArangoDB or production graph database experience, search and information-retrieval fundamentals, front-end or full-stack experience, MLOps and evaluation frameworks, model adaptation and inference optimization, relevant industry experience, and security and compliance familiarity.
Benefits
- Remote role based in San Francisco, California.
- Opportunity to work on AI and data infrastructure, collaborate with experienced technical and business teams, and shape enterprise AI applications.
Tech Stack
Apache AirflowApache KafkaAWSAzureDockerFastAPIGitHub ActionsGoogle BigQueryGoogle Cloud PlatformGrafanagRPCKubernetesMLflowNext.jsPostgreSQLPrometheusReactSnowflakeTerraformTypeScript
Categories
Solutions Engineering