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,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