GenAI Engineer

**About Clarity** We’re pioneering **Agentic AI** — systems that don’t just respond, but **reason, act, and adapt** autonomously in complex workflows. This is about crafting **AI Agent Experiences** — designing agents that collaborate seamlessly with humans, learn from context, and make every customer interaction faster, smarter, and more empathetic. You’ll own the technical vision and turn requirements into a live, reliable product used by brands like **Grubhub,** [****](http://Booking.com)**, Dropbox, Uber, Careem, and Fubo**. You’ll collaborate directly with engineers, other tech leads, directors, and the CTO to evolve ambitious prototypes into a rock‑solid, scalable platform What you’ll actually do **50% Build — design & ship** - **Agentic AI for CX:** Real‑time assistants that listen to calls/chats, retrieve from customer KBs, and draft responses with human‑in‑the‑loop controls. - **Structured extraction:** Schema‑driven pipelines over unstructured text (and other modalities) using retrieval, tool‑use, and robust LLM prompting. - **Hybrid anomaly detection:** Blend classical time‑series methods (e.g., decomposition, change‑point, forecasting) with LLM‑aware, contextful detectors for seasonality, spikes, step‑changes, and drift. - **Novelty discovery:** Embedding‑based clustering and drift, topic surfacing, LLM summarization of emerging themes with deduplication and evidence links. - **Alerting & scoring:** Severity/impact ranking, de‑noising, suppression/cool‑downs, routing, and feedback loops. **25% Architect & scale** - Own reliability, latency, and cost. Design online/offline eval harnesses, canaries, and SLAs; operate GPUs/accelerators where needed. - Stand up and harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. - Take basic infra ownership on **GCP** (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost tuning. - Participate in on‑call for your area and drive root‑cause analysis with crisp follow‑ups. **15% Collaborate** - Pair with back‑end & front‑end to wire extractors/detectors and agents into ticketing, voice, and analytics stacks (APIs, webhooks, real‑time streams). - Partner with PMs/CX to evolve taxonomies, schemas, and guardrails; translate business problems into shipped ML features. **10% Align & showcase** - Gather requirements from CX and product leads, demo new capabilities to execs & customers, and document impact with precision/recall, alert quality, latency, and cost metrics. **What makes you a great fit** - **Startup hacker mindset:** You self‑start from zero, respect no silos, and carry work from prototype to production. 🛠️ - **AI‑native dev tools are your daily drivers:** Cursor, v0, Claude Code (or similar). - **7–10 years** building production ML/back‑end systems; **2+ years** leading while coding. - **Expert Python**; strong back‑end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams). - **Agents & RAG:** Fluency with at least one agent framework (**ADK preferred**). Proven track record shipping AI agents and building RAG pipelines. - **LLM + DS depth:** Prompting/tooling, retrieval design, LLM evals; hands‑on with time‑series analysis (forecasting, change‑point, drift). - **Cloud & ops:** Basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost control. - **Communication:** You explain results clearly, align stakeholders, and write crisp docs. **Bonus points** - DevOps wizardry; GPU/accelerator experience. - Multimodal pipelines (text + voice + screenshots). - Prior experience in contact center/CX analytics or novelty/anomaly systems. - Founder or founding engineer experience