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