Key Responsibilities
AI Product Development
Design, build, and maintain AI-driven applications and services, including front-end and back-end components.
Collaborate across teams to integrate AI features into customer-facing and internal products.
GenAI & Voice AI Integration
Implement cutting-edge frameworks (e.g., LangChain, LlamaIndex, Agent SDKs) to enable advanced GenAI and multimodal use cases.
Develop voice-enabled features using STT, TTS, and real-time voice synthesis for conversational interfaces.
Agentic AI & A2A Protocols
Design and deploy agentic AI systems with tool-using, multi-step reasoning capabilities.
Enable agent-to-agent (A2A) interactions for coordination, delegation, and multi-agent task execution across systems.
RAG & LLMOps Engineering
Build and maintain retrieval-augmented generation (RAG) pipelines and model fine-tuning workflows.
Establish robust LLMOps practices—covering versioning, prompt management, automated evaluations, monitoring, and CI/CD for AI.
API & Data Infrastructure
Develop secure, scalable RESTful APIs and data pipelines to support both real-time and batch AI applications.
Work with structured and unstructured data using relational and NoSQL databases.
Testing, Optimization & Reliability
Write unit/integration tests, monitor production performance, and optimize AI systems for latency, uptime, and scalability.
Cross-Team Collaboration
Work closely with product managers, designers, and engineers across regions (e.g. UK, EU, USA, AU).
Mentor junior engineers and help define AI development best practices.
Requirements
5+ years of experience in machine learning, NLP, or applied AI
Proven experience with LLMs (OpenAI, Claude, Mistral, open-source models), vector databases, and orchestration frameworks
Demonstrated ability to build RAG systems , fine-tune foundation models, and design agentic AI architectures
Hands-on experience with A2A, MPC protocols or frameworks for multi-agent collaboration
Strong Python development skills and back-end experience building scalable APIs and microservices
Deep understanding of LLMOps : versioning, evaluation frameworks, model observability, CI/CD for AI/ML
Experience with cloud platforms (AWS, GCP, or Azure) and secure, distributed AI infrastructure
Familiarity with Voice AI technologies (Whisper, Deepgram, ElevenLabs) is a strong plus
Background in experimentation frameworks (A/B testing, reinforcement learning)
Strong communication and collaboration skills in cross-cultural, distributed environments
Why choose us
At Flutter CEE, people have access to vast opportunities for career growth and self-development. Our employee benefits package goes far beyond offering the minimum: We support our people in becoming their best version at work and beyond - and our benefits reflect that commitment.
These are some of the benefits included in our employee package:
Generous annual leave
Hybrid work
Individual health insurance
Paid sick leave
Paid maternity & paternity leave
Family reward
Performance & referral bonuses
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