15h Left: Senior Ai Engineer

Job Overview We re hiring an Senior AI Engineer to build production-grade components for an AI-first data-centric platform You will implement agentic capabilities intent planner router composer integrate knowledge-graph reasoning alongside a strong RAG baseline and instrument robust evaluation and observability The ideal candidate writes clean reliable code understands LLM systems and data retrieval trade-offs and can optimize for latency quality and cost Key Responsibilities Agent Implementation Build and harden Intent Planner and Router Composer agents with typed JSON I O retries timeouts and idempotency emit call-graph traces and correlation IDs Knowledge-Graph Reasoning Generate correct graph queries SPARQL Gremlin PGQL from planner outputs perform subgraph extraction encode rationale and references in responses RAG Baseline Retrieval Implement document prep chunking embeddings hybrid retrieval and where available reranking maintain a high-quality baseline path for side-by-side comparisons Prompt Config Tuning Version and tune prompts routing policies small large model escalation temperature top-p settings and caching document routing outcomes and cost latency budgets Evaluation Hooks Integrate test sets and scoring faithfulness correctness precision recall multi-hop coverage latency enable automated re-evaluation on any change model agent prompt data Observability Cost Controls Instrument traces metrics logs token usage latency P50 P95 error codes surface cost-per-answer dashboards implement backpressure and graceful degradation Security Guardrails Enforce policy-as-code and entitlement checks role row column PII PHI handling content moderation and HITL approval prompts for state-changing actions Quality CI CD Write unit integration contract tests participate in PR reviews ship via CI CD with feature flags and environment promotion maintain API connector schemas and docs Required Skills Applied LLM Engineering 1-2 years building production services hands-on with LLM tool function-calling agent frameworks and prompt version management Knowledge Retrieval Practical experience with Knowledge Graphs RDF SPARQL or property graph Gremlin and RAG pipelines chunking embeddings retrieval reranking Data Model Ecosystem One or more vector DBs pgvector Pinecone Weaviate Milvus and search OpenSearch Elasticsearch familiarity with major model platforms Azure OpenAI Vertex Anthropic open-weights Backend Skills Proficiency in Python and or TypeScript Node js strong REST gRPC API design JSON Schema OpenAPI retries backoff idempotency and error taxonomies Observability Reliability OpenTelemetry traces metrics logs performance profiling resiliency patterns circuit breakers bulkheads DLQ queues Security by Design OIDC SSO secrets management least-privilege access audit logging and secure coding for AI data services CI CD Testing Git-based workflows automated pipelines unit integration contract tests and environment promotion practices Good to Have Skills Ontology Data Quality SHACL OWL basics ontology stewardship lineage provenance capture and data quality checks for KG RAG pipelines Evaluation Engineering Judge-model setups A B testing rubric design and regression dashboards Performance FinOps Async I O caching strategies connection pooling and token runtime budget enforcement Runtime Platform Containers Kubernetes service mesh API gateways feature flags blue green or canary releases UX for Explainability Collaborating on rationale explanations source lists subgraph summaries and clear HITL approval prompts This role is ideal for a hands-on engineer who enjoys turning advanced reasoning patterns into robust observable services-balancing quality safety and cost at enterprise scale