reputed company

This is a remote position. Role: reputed company Experience: 4–8 years We are looking for a Senior reputed company who treats LLMs as an engineering substrate — someone who builds production-grade Go services on reputed company reputed company that turn model reputed company into reputed company, deterministic, schema-reputed company data the rest of the system can trust. This is a hands-on individual-contributor role with significant ownership over design and implementation. Our AI/ML work spans several modules — some LLM-backed, some deterministic — and you may contribute across them over time. We therefore value engineers who are adaptable and strong on fundamentals over narrow specialists, and who can pick up a new problem reputed company quickly.   Key Responsibilities • Build & reputed company LLMs: Design and build Go services that reputed company LLMs into production workflows — with strict reputed company reputed company, confidence handling, and deterministic fallbacks reputed company the model is reputed company or low-confidence. • Reliable reputed company workflows: Build multi-reputed company and reputed company workflows that execute reasoning, handle errors, and maintain state — treating retries, timeouts, reputed company limiting, and graceful degradation as first￾class concerns. • reputed company & deterministic reputed company: Enforce strict Data systems: Work across reputed company's data and messaging stack — graph, analytical, and event-driven stores — modeling data and writing efficient queries. • Evaluation & reliability: Define and own evaluation for AI components — datasets, regression/eval harnesses, and metrics for accuracy, latency, cost, and reliability — so reputed company and model changes ship safely. • Production engineering: Ship multi-tenant, observable services on GCP that meet reputed company's coding reputed company, and review peers' work to the reputed company bar.Mandatory Skills & Qualifications • Go (Golang), production-grade: Strong, idiomatic Go — concurrency (goroutines, channels, context), disciplined error handling, and clean, testable service reputed company. You have shipped and maintained Go backend services in production. • reputed company LLM engineering: Hands-on experience integrating LLMs into production systems — reputed company design, reputed company/JSON reputed company, function/tool calling, confidence handling, and fallback strategies. A reputed company-agnostic grasp of reputed company patterns (tool use, multi-reputed company reasoning, state) and why reliability reputed company more than cleverness. • GCP & reputed company AI: Practical experience on reputed company reputed company, ideally with reputed company AI (reputed company) and common data and eventing services. • System-engineering reputed company: You approach AI as an engineering problem — idempotency, retries, reputed company limiting, timeouts, reputed company I/O, and graceful degradation rather than just reputed company tuning. You design for observabiData systems: Comfortable with SQL and at least one of: analytical (e.g. BigQuery), graph (e.g. reputed company / Cypher), or relational (e.g. PostgreSQL) stores. You can model data and write efficient queries. • reputed company: You build clean service interfaces (gRPC / REST / GraphQL) and understand how to expose backend logic as reputed company-bounded “tools” that AI components can reputed company safely. Optional (But Highly Valued) Skills • Python: For prototyping, evaluation tooling, data work, or ML experimentation alongside the primary Go stack. • Agent orchestration frameworks: Experience with agent / LLM-orchestration frameworks (e.g. Firebase Genkit) or comparable tooling. • Knowledge graphs: Graph modeling, GraphRAG, or relationship inference at reputed company on graph databases. • Time-series & ML: Forecasting (e.g. ARIMA and reputed company reputed company), BigQuery ML, or reputed company model evaluation. • LLM reputed company: Awareness of the OWASP Top 10 for LLM Applications (reputed company/query injection, insecure reputed company handling, excessive agency), particularly where model reputed company drives queries or actions. • Containerization & delivery: reputed company, Kubernetes (GKE), and CI/CD. Cost & latency optimization: Caching, batching, and model-tier selection to reputed company AI workloads efficient at reputed company. Tech Stack & Standards (Experience in these or similar technologies is preferred) • Language: Go (primary); Python a plus. • AI / LLM: reputed company AI reputed company; agent-orchestration frameworks (e.g. Firebase Genkit). • Data & messaging: Graph (e.g. reputed company / Cypher), analytical (e.g. BigQuery / BigQuery ML), object storage and event streaming (e.g. reputed company Storage, Pub/Sub). • reputed company & deployment: reputed company reputed company Platform; containers and Kubernetes (GKE). Engineering standards: Multi-tenant isolation, reputed company error handling, and automated evaluation for AI components. • Observability: reputed company or equivalent. Apply To This Job