Artificial Intelligence Engineer ID42044

Artificial Intelligence Engineer Senior AI Engineer role focused on building AI-powered systems that turn complex data into actionable insights. You will shape technical direction, influence team culture, and apply AI-first thinking to real-world problems, driving innovation and measurable business value in a fast-paced, collaborative environment. Responsibilities Build AI applications: Design and deploy intelligent systems that parse tariffs, optimize utility spend, and automate workflows—shipping production-grade features quickly while maintaining quality. Document-centric RAG with OpenAI: Implement RAG using structured tool/JSON outputs, streaming and batch flows, with robust guardrails, red-teaming, and RAG evaluation (e.g., RAGAS, TruLens). Productionize agent workflows: Integrate cutting-edge AI models into resilient pipelines and services that run reliably in real-world environments. Scraping/ingestion at scale: Create pipelines for automated utility logins → parse/store bills & usage → anomaly detection → “ready-to-audit” bills, with full auditability and data lineage. Production services on cloud: Build and operate on GCP (Cloud Run and/or GKE); use BigQuery as the analytics backbone feeding Looker; leverage Firestore for app state and permissions. (AWS experience transferable.) APIs & full-stack delivery: Develop APIs and backend services in Python/TypeScript and collaborate with frontend integrations as needed. Reliability, cost & latency controls: Lead feature-flagged rollouts, implement end-to-end tracing, and enforce p95/p99 SLOs, budgets, and rate-limiting to balance performance and spend. Iterate rapidly: Prototype, test, and launch features fast; harden successful prototypes into scalable, observable, secure services. Shape foundations: Establish engineering standards, architecture principles, and AI-first practices that set the bar for the company. Qualifications MUST HAVES Experience level: 4+ years as a software engineer and at least 2+ years at an AI-first company or building AI-powered applications. Production engineering: Professional experience building and maintaining APIs, data pipelines, or full-stack applications in Python and TypeScript. LLM workflow deployment: Hands-on deploying AI/LLM workflows to production (e.g., LangChain, LlamaIndex, orchestration frameworks, vector databases). Startup DNA: Thrives in ambiguity, bias to action, problem-first mindset, and high ownership. RAG in production: Proven track record shipping document-centric RAG (retrieval, chunking, embeddings/vector DBs, re-ranking) with OpenAI, structured tool/JSON outputs, and streaming responses. RAG evaluation: Hands-on use of RAGAS and/or TruLens with measurable quality gates. Guardrails & safety: JSON Schema/Pydantic validation, moderation and grounding checks, plus red-teaming practices in production. Cloud production (GCP-first): Experience operating services on Cloud Run/GKE, using BigQuery (consumed in Looker) and Firestore for app state/permissions; strong CI/CD discipline. (AWS familiarity is a plus/transferable.) Scraping/ingestion at scale: Built and operated pipelines with authentication, robust parsing/storage, and audit-ready artifacts (data lineage, repeatability). Observability & controls: Structured logging, tracing (OpenTelemetry), metrics; cost/latency guardrails and safe releases (feature flags, canary, rollback) meeting p95/p99 SLOs. English: Upper-Intermediate English level. NICE TO HAVES Experience with parsing unstructured data, optimization algorithms, or time-series forecasting. Background in energy, utilities, or IoT data (not required, but valuable context). Prior experience in a founding or early-stage engineering role. Vector databases (pgvector, Pinecone, Weaviate) and re-ranking experience. GCP IaC (Terraform), Secrets/IAM hardening; Looker/LookML modeling. Perks & Benefits Professional growth: Mentorship, TechTalks, and personalized growth roadmaps. Competitive compensation: USD-based compensation with budgets for education, fitness, and team activities. A selection of exciting projects: Projects with modern solutions and top-tier clients, including Fortune 500 enterprises. Flextime: Flexible work options for work-life balance, including remote and office options. Note: This description reflects the current role responsibilities and qualifications. Referrals information and additional job postings listed on the page have been omitted for clarity. #J-18808-Ljbffr