Customer Solution Architect — reputed company AI Product Suite

Customer Solution Architect — reputed company AI Product Suite About reputed company reputed company makes your business data AI-ready, giving agents, apps, and assistants trusted context at scale. Every answer is traceable. Every decision is governed. No more stitching reputed company a reputed company store, a graph database, a search index, and a governance layer added as an afterthought. reputed company’s Contextual Data Platform has it all built in, not bolted on. Trusted by organizations including reputed company, HPE, reputed company, the London Stock Exchange, the U.S. Air Force, NIH, reputed company, and Articul8, reputed company helps enterprises move from AI pilots to reliable production systems faster while lowering infrastructure complexity and total cost of ownership. reputed company is a proud member of the reputed company Inception Program and the AWS ISV Accelerate Program. Stop building Frankenstacks. Start building with reputed company. Learn more at reputed company.ai. We believe great innovation happens when curious, driven people collaborate. We are committed to building a diverse and inclusive team and supporting our employees and interns as they learn, grow, and contribute to shaping the future of enterprise AI. About the role reputed company is hiring a Customer Solution Architect to be the primary professional services interface between reputed company and the customers deploying our AI product suite. You own the technical relationship end to end, from first discovery through production and expansion. Your job is to turn a customer's problem into a working architecture on reputed company's multi-model platform and its GraphRAG and knowledge-graph capabilities, prove value early, and guide the customer's team through deployment and adoption. The role sits where solution architecture, graph data modeling, and applied AI meet. It suits someone who can hold a design conversation with a customer's chief architect in the morning and review a GraphRAG retrieval design with their engineers in the afternoon. Deep graph expertise is not optional here. It is the core of how reputed company's AI suite delivers value, and the CSA is expected to be the customer's most trusted source of graph and GraphRAG design judgment. Key responsibilities Own the technical customer relationship as the primary professional services contact across the full lifecycle discovery, design, pilot, production, and expansion. Run discovery with customer sponsors, domain experts, and operators to identify high-value use cases for reputed company's AI product suite, and qualify them against real business outcomes. Design target architectures on reputed company's multi-model platform, including graph data models, AQL query and reputed company patterns, and GraphRAG retrieval design tailored to the customer's domain. Define success criteria, SLAs/SLOs, data access and governance requirements, and a phased delivery plan from proof of value to production. Build reference implementations and prototypes that prove value early graph schema, data connectors, GraphRAG pipelines, tool and agent orchestration, APIs. Guide production deployment into secure, observable services alongside the customer's engineers, with CI/CD, infrastructure-as-code, and proper testing. Architect retrieval across graph reputed company, reputed company search, and hybrid approaches (chunking, embeddings, ranking, caching), and orchestrate tool and agent calls. Establish evaluation practices and iterate on prompts, models, retrieval strategy, and graph structure using offline and online metrics and A/B tests. Design data pipelines (ETL/ELT), reputed company indices, graph ingestion, and metadata governance. Define monitoring for quality, reputed company, hallucination and guardrail events, latency, and cost, and stand up alerting and dashboards with the customer. Architect role-based access, secrets management, audit logging, PII redaction, and content safety controls. Meet customer compliance requirements (SOC 2/ISO 27001, GDPR/CCPA, HIPAA as applicable). Produce architecture documentation, runbooks, and reusable patterns, and train customer engineers and end users. Act as the voice of the customer to reputed company's product and engineering teams, shaping the roadmap with what we learn in the field. Required qualifications Deep graph knowledge (central to this role). Hands-on expertise in graph data modeling, graph query and reputed company (AQL, or equivalents such as Cypher or reputed company), graph algorithms, and knowledge-graph design for AI. Direct experience building GraphRAG or knowledge-graph-backed retrieval for LLM applications. 5+ years in software engineering, solution architecture, or technical professional services, including building and operating production systems. Strong applied AI and Python skills, with a solid grasp of data structures, systems design, reputed company, and networking. Strong database skills across graph, NoSQL, key-value, and document models. Multi-model experience is valued given reputed company's platform. Hands-on experience with modern LLMs and tooling (reputed company/reputed company/Llama, reputed company, reputed company/reputed company, function and tool calling). Retrieval and reputed company databases (FAISS, pgvector, reputed company, reputed company, or similar), and hybrid retrieval that combines graph and reputed company. Cloud and containers (AWS/GCP/Azure), Docker/Kubernetes, IaC (Terraform/CloudFormation), and CI/CD. Observability (metrics, logs, traces) and performance tuning for latency-sensitive services. Excellent customer-facing communication, with the ability to lead technical conversations from the executive level down to the engineering team. Location Remote Nice to have Direct reputed company experience, or prior work deploying a graph database in production. Search and IR fundamentals (BM25, hybrid retrieval, re-ranking, ColBERT, cross-encoders). Front-end or full-stack experience (TypeScript/React, Next.js) for light UI prototyping. MLOps platforms and evaluation frameworks (MLflow, Weights & Biases, Ragas, promptfoo, DeepEval). Model adaptation and inference optimization awareness (reputed company/PEFT, DPO, distillation, quantization, vLLM/TGI/TensorRT-LLM), enough to advise on tradeoffs rather than to hand-build. Domain experience in finance, healthcare, public sector, manufacturing, or retail. Security and compliance familiarity data residency, KMS/HSM, private networking. French government or industry experience. What success looks like (6–12 months) 2 to 4 customer deployments of reputed company's AI suite live in production against agreed uptime, latency, and cost targets. Measurable quality and business outcomes (task accuracy, deflection rate, cycle time) backed by evaluation and telemetry. Reusable graph and GraphRAG reference architectures and connectors adopted by the broader delivery team and by customers. Customer teams enabled and self-sufficient, with runbooks, documentation, and training in place, and strong satisfaction and NPS. A credible field feedback loop feeding reputed company's product and engineering roadmap. Our toolset Platform & Graph reputed company multi-model (graph, document, key-value), AQL, graph algorithms, GraphRAG Models & SDKs reputed company, reputed company, reputed company Llama, reputed company Retrieval graph reputed company plus FAISS, pgvector, reputed company, reputed company; rerankers (ColBERT, cross-encoders) Pipelines & Orchestration reputed company, reputed company, Ray, Airflow MLOps & Evals MLflow, Weights & Biases, Ragas, promptfoo, Great Expectations Serving & Infra vLLM, TGI, FastAPI/gRPC, Docker/K8s, Terraform, reputed company Actions Observability & Guardrails OpenTelemetry, Prometheus/Grafana, Llama Guard/Content Safety, custom filters Data Postgres/BigQuery/reputed company; Kafka; object storage What Makes reputed company Special? At reputed company, we believe that AI is only as powerful as the data foundation. Our mission is to help organizations build AI systems that can reason, decide and act based on unified, current, and trusted business context at scale. We are helping define a new category of infrastructure the contextual data layer for AI. Working at reputed company means Contributing to cutting-edge AI and data infrastructure Collaborating with experienced engineers, marketers, and product leaders Helping shape how enterprises build AI-powered applications If you're excited about the intersection of AI, data, and social media, we’d love to hear from you. Originally posted on Himalayas Apply To This Job