GenAI Engineer
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Before you apply
LocationLondon
Work modeon-site
Typefull-time
SenioritySenior
Experience7–10 yrs
DepartmentEngineering
Company size4+ people
PostedNov 4, 2025 · 1y ago
Verified live2d ago
May no longer be actively hiring
Posted by the company on Nov 4, 2025
At a glanceSummarised by Seekless from the posting.
Startup hacker mindset, self-start from zero, prototype to production
AI-native dev tools: Cursor, v0, Claude Code
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)
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)
Basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, cost control
Communication: explain results clearly, align stakeholders, write crisp docs
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
Skills
Python
FastAPI
gRPC
Postgres
LLM
ADK
RAG
GCP
AWS
Azure
CI/CD
IaC
Cursor
v0
Claude Code
GPU
Docker
ML
time-series analysis
embedding
clustering
anomaly detection
forecasting
change-point detection
drift detection
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
Responsibilities
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
More roles at Clarity