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For Companies At a Glance
- Tasks: Lead the tech vision, build AI products, and collaborate with engineers.
- Company: Anecdote is an innovative startup transforming customer feedback analysis with AI.
- Benefits: Enjoy remote work, flexible hours, unlimited vacation, and a learning budget.
- Why this job: Join a dynamic team shaping AI solutions for top brands and making a real impact.
- Qualifications: 7-10 years in ML/backend systems, expert in Python, and experience with LLMs.
- Other info: Participate in regular off-sites and monthly virtual game nights.
The predicted salary is between 43200 - 72000 £ per year.
Anecdote is building the AI Hub—a unified platform that powers domain-specific AI agents - a real-time copilot that listens to live calls or chats, reads our customers’ knowledge base, and drafts perfect replies for human agents. As the Tech Lead, you will own the technical vision and will be turning the technical requirements into a live product. Collaborate directly with engineers, engineering directors, CTO, and other tech leads to turn ambitious prototypes into a rock-solid product used by brands like Grubhub, Booking, Dropbox & Uber.
Anecdote is an innovative, AI-first startup revolutionising how companies analyse customer feedback. Our AI-powered platform consolidates feedback from app reviews, support chats, surveys, and social media into a single, easily accessible space. This enables companies like Grubhub, Dropbox, and Careem to derive actionable insights and deliver a better, real-time customer experience that drives sustainable growth. We are backed by top investors, including Neo, Sukna, Race Capital, Propeller, and Wamda, having raised $3.5m to date.
What you will actually do
- 50% Build: Write critical Python, design APIs, fine-tune LLMs, create evaluation harnesses, and ship to production.
- 25% Architect and scale: Architect & operate scalable GPU clusters on GCP (Vertex AI / GKE / Cloud Run). Monitor cost, latency, and reliability; own the on-call.
- 15% Collaborate: Pair with backend & front-end engineers to wire RAG pipelines into ticketing, voice, and analytics stacks.
- 10% Align & Showcase: Gather requirements from CX leads, demo new capabilities to execs & customers, and document impact.
Requirements
- 7-10 years building production ML / backend systems, including 2+ years leading while coding.
- Expert Python; solid back-end skills (FastAPI, gRPC, Postgres, pub/sub).
- Experience in ML and Data Science.
- Using AI-first IDE like windsurf and cursor every day.
- Proven record deploying & tuning open-source LLMs (DeepSeek, Llama) on GPUs.
- Fluency with at least one agent framework (preferably ADK) and RAG pipelines.
- Strong infrastructure ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, cost tuning.
- Track record translating business problems into shipped ML products—and presenting results in plain English.
- Bonus: DevOps skills, multimodal pipelines, prior relevant experience.
Perks and bonuses
- Remote-first freedom & flexible hours.
- Regular off-sites & monthly virtual game nights.
- Unlimited vacation (minimum 20 days encouraged).
- Learning budget for conferences, courses & books.
- Startup equity in a rapidly growing market.
Contact Detail:
Anecdote Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GenAI Tech Lead
✨Tip Number 1
Familiarise yourself with Anecdote's AI Hub and the specific technologies they use, such as Python, FastAPI, and GCP. Understanding their platform will help you speak confidently about how your skills align with their needs during discussions.
✨Tip Number 2
Network with current or former employees of Anecdote on platforms like LinkedIn. Engaging in conversations can provide you with insider insights about the company culture and expectations, which can be invaluable during interviews.
✨Tip Number 3
Prepare to discuss your experience with deploying and tuning open-source LLMs. Be ready to share specific examples of projects you've worked on that demonstrate your expertise in this area, as it’s a key requirement for the role.
✨Tip Number 4
Showcase your ability to translate complex technical concepts into simple terms. Anecdote values clear communication, so practice explaining your past projects in a way that highlights their impact on business outcomes.
We think you need these skills to ace GenAI Tech Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in building production ML and backend systems. Emphasise your leadership roles and technical skills, especially in Python and relevant frameworks like FastAPI and gRPC.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your background aligns with Anecdote's mission. Mention specific projects where you've successfully deployed and tuned open-source LLMs, showcasing your ability to translate business problems into ML products.
Showcase Relevant Projects: Include a portfolio or a section in your CV that details relevant projects. Highlight your experience with GPU clusters on GCP, your work with RAG pipelines, and any innovative solutions you've implemented in previous roles.
Prepare for Technical Questions: Anticipate technical questions related to your expertise in ML, backend systems, and infrastructure ownership. Be ready to discuss your experience with cost tuning, CI/CD, and how you approach problem-solving in a collaborative environment.
How to prepare for a job interview at Anecdote
✨Showcase Your Technical Expertise
As a GenAI Tech Lead, you'll need to demonstrate your deep understanding of Python and backend systems. Be prepared to discuss your experience with FastAPI, gRPC, and deploying open-source LLMs. Highlight specific projects where you've successfully turned technical requirements into live products.
✨Emphasise Collaboration Skills
Collaboration is key in this role. Share examples of how you've worked with engineers and other tech leads to achieve common goals. Discuss your approach to gathering requirements from stakeholders and how you ensure alignment across teams.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your ability to translate business problems into ML solutions. Prepare to explain your thought process and the steps you take to develop and implement effective strategies. Use real-life examples to illustrate your problem-solving skills.
✨Demonstrate Your Passion for AI
Anecdote is an AI-first startup, so showing your enthusiasm for AI technologies is crucial. Discuss any personal projects or continuous learning efforts related to AI and machine learning. This will help convey your commitment to staying at the forefront of the industry.
