About Ahenk AI

Building the Future of Agentic AI

Ahenk AI democratizes autonomous AI agents through a powerful no-code platform. We enable anyone, from individual creators to global enterprises, to build, deploy, and orchestrate intelligent agents without technical barriers.

Cloud or on-premise. Simple or sophisticated. One platform for all your agentic AI needs.

The Role

We're building production-grade AI agent systems that need to work across different cloud platforms and scale from individual users to enterprise deployments. You'll architect intelligent agents using the latest foundation models, build robust infrastructure that spans GCP and AWS, and solve complex problems around model performance, cost optimization, and reliability.

This role combines research and engineering. You'll experiment with new model architectures and prompting techniques, then deploy those innovations to production where they'll power real workflows. Your work will range from fine-tuning models for specific domains to building multi-agent systems that collaborate on complex tasks.

This is a full-time, remote position based in London, UK.

What You'll Do

• Design and deploy AI agent architectures on both GCP (Vertex AI) and AWS
• Build and optimize RAG pipelines with vector databases, hybrid search, and semantic chunking strategies
• Fine-tune and deploy large language models for domain-specific tasks, including LoRA, QLoRA, and full parameter tuning
• Develop multi-agent orchestration systems with tool use, memory, and autonomous decision-making capabilities
• Train smaller, specialized models from scratch when they outperform larger general-purpose alternatives
• Implement evaluation frameworks to measure and improve agent performance across different tasks
• Build data pipelines using BigQuery and Redshift to feed high-quality data into training and inference
• Deploy and scale AI workloads on Kubernetes (GKE, EKS) with proper monitoring and observability
• Collaborate with product teams to translate user needs into technical specifications and working systems
• Maintain production systems with CI/CD pipelines, automated testing, and continuous model monitoring

What You Bring

• 5+ years building production ML/AI systems, with at least 2 years working extensively with LLMs and generative AI
• Hands-on experience with multiple cloud platforms, particularly GCP and AWS
• Deep understanding of transformer architectures, attention mechanisms, and how modern language models actually work under the hood
• Production experience training or fine-tuning language models, including knowledge of optimization techniques, learning rate schedules, and debugging training runs
• Practical experience building RAG systems that handle real-world data at scale, including chunking strategies, embedding selection, and retrieval optimization
• Strong prompt engineering skills with techniques like chain-of-thought, few-shot learning, and function calling
• Experience with model deployment and serving, including quantization techniques (GGUF, AWQ, GPTQ) for efficient inference
• Expert Python skills with production-quality code and strong understanding of async programming patterns
• Proficiency with TensorFlow, PyTorch and familiarity with Hugging Face ecosystem for model development
• Solid understanding of Docker, Kubernetes, and cloud-native deployment patterns
• Experience building data pipelines and working with both structured and unstructured data at scale
• Bachelor's degree in Computer Science, Engineering, or related field (Master's or PhD preferred)

Bonus Points

• Knowledge of distributed training techniques (DDP, FSDP, DeepSpeed) for multi-GPU setups
• Familiarity with modern inference optimization (vLLM, TGI, TensorRT-LLM) for low-latency serving
• Experience with reinforcement learning from human feedback (RLHF) or direct preference optimization (DPO)
• Experience with JAX for high-performance numerical computing
• Contributions to open-source ML/AI projects or publications at top-tier conferences (NeurIPS, ICML, ICLR)
• GCP Professional ML Engineer or AWS ML Specialty certification

Why Ahenk AI?

We're a small team solving hard problems in agentic AI. You'll have real ownership over the systems you build, work with the latest AI technologies, and see your work used by users ranging from individual developers to large organizations.

You'll experiment with new model architectures, optimize for performance and cost, and make architectural decisions that shape our product. We value both technical excellence and pragmatic shipping. We're remote-first with flexible working hours and a culture that promotes continuous learning.

This is an opportunity to work on challenging technical problems while building something that makes powerful AI accessible to more people.

Our Commitment to Diversity

At Ahenk AI, we're building a team as diverse as the problems we solve. We believe different perspectives make us stronger, and we're committed to creating an inclusive environment where everyone can do their best work. We're an equal opportunity employer and welcome applications from all backgrounds.

Ready to Apply?

If this role resonates with you, we encourage you to apply, even if you don't meet every requirement. Research shows that women and underrepresented groups often hesitate to apply unless they match 100% of the criteria. We believe diverse perspectives make us stronger, and we value passion and potential just as much as experience.

Ahenk AI is a proud participant in the Tech Nation Global Talent programme.