LLM Platform Engineer/Lead (m/f/d)
LLM Platform Engineer/Lead (m/f/d)
Berlin, Bangalore, Remote
Hello 👋 I am Servesh, Co- founder and CTO at Kayzen, and I am now looking for a LLM Platform Engineer/Lead who will be part of our Engineering team. 🙌 But wait, you have not heard of Kayzen before? 😃
Kayzen is a mobile demand-side platform (DSP) dedicated to democratizing programmatic advertising. We enable leading apps, agencies, media buyers, and brands to run programmatic customer acquisition, retargeting, and brand performance campaigns through its self-serve and managed service options. Built on the three core pillars of performance, transparency, and control, Kayzen powers the world’s best mobile marketing teams with bespoke solutions that fuel business growth and deliver a competitive advantage. With an unprecedented scale of 160B+ daily ad requests from 1.6B+ unique users worldwide, we serve up to 1B+ ads per day in 180 countries. Kayzen is accessible through our APIs and user interface.
The Team
The Platform Engineering team owns Real-time bidding (RTB) platform, a Real-time budget system, Real-time event processing, Stream data processing engine and multiple other complex large-scale distributed components and data pipelines. We work closely with data scientists, data analysts, product and business teams. We are responsible for some of the most technically challenging work, for example:
- Handling ~2 Million Req/sec in sub-millisecond latency
- Handing & managing ~Petabytes of data
- Managing distributed systems deployed across multiple data centers
- Optimizing JVM and Linux kernel for optimal performance
- Managing our own data center spread across the globe consisting of thousand of powerful servers
- Working on some of the most challenging problems of Ad-Tech
Sounds interesting. Isn't it?
About the Role
We are looking for an LLM Platform Engineer /Lead who can evangelise AI across the company and build the foundational tooling, frameworks, and workflows that allow teams to ship AI-powered features quickly and safely. This role is ideal for an engineer who understands modern AI capabilities and focuses on developer velocity, reuse, and production readiness rather than training complex models from scratch.
Responsibilities
- Design and build internal AI frameworks, SDKs, and shared libraries
- Enable teams to integrate AI features with minimal friction
- Set up standardized patterns for using LLMs, embeddings, agents, and workflows
- Build reusable components for prompt management, evaluation, observability, and safety
- Define best practices for AI usage, cost control, and reliability
- Evangelise AI internally through documentation, examples, and hands-on guidance
- Rapidly prototype AI-powered features and turn them into reusable building blocks
- Own AI tooling from experimentation to production
Requirements
AI Tooling & Framework Experience (Core Focus)
- Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.)
- Experience with RAG pipelines, embeddings, vector databases
- Familiarity with prompt engineering, prompt versioning, and evaluation
- Experience with AI orchestration frameworks
- Understanding of AI observability, cost monitoring, and failure modes
- You’ve shipped at least one LLM-powered feature to production and iterated based on telemetry or user feedback.
- Comfortable with embeddings, fine-tuning, vector search, tokenization, and evaluation methodologies.
- Familiar with data lakes/warehouses, feature stores, and streaming/batch ETL; cloud (AWS/GCP/Azure).
Strong Engineering & Platform Skills
- Excellent Python skills (required)
- Experience building frameworks, platforms, or developer tooling
- Strong understanding of APIs, services, and system design
- Writes clean, maintainable, production-grade code
Startup Mindset
- Bias for shipping and iteration
- Can translate AI complexity into simple abstractions
- Comfortable with ambiguity and rapid change
- Thinks in terms of leverage and reuse , not one-off solutions
Less About
- Heavy model training or research
- Designing custom ML algorithms
- Academic optimization work.
Nice to have
- Experience with agent-based systems and tool calling
- Experience setting up guardrails, moderation, and safety checks
- Familiarity with Docker, cloud infra, and CI/CD
- Prior work in platform teams or enablement roles
What do we offer?
- Reporting directly to Co-founder & CTO
- Direct access to top management and an extremely “visible” role
- Exceptional career growth and learning opportunity
- A unique opportunity to be part of an experienced team of industry experts and entrepreneurs who bring massive change to the Adtech market
- A fun, driven, and multinational team located across Germany, India, UK, Argentina, Ukraine, Turkey, Spain and many more countries
- A flexible work-from-home arrangement
- A 500-dollar home-office setup budget
- A 1000-dollar annual learning and development budget