- Salary
- €60k – €72k/yr
- Location
- Sofia/Plovdiv
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Source
- Pinpoint
Description
Senior AI Platform Engineer
Department: Engineering
Employment Type: Full Time
Location: Sofia/Plovdiv
Compensation: €60,000 - €72,000 / year
Description
We are looking for a Senior AI Platform Engineer to own the operational excellence, infrastructure, and deployment pipelines for our AI platform. You'll do more than support AI systems. You'll shape and evolve the platform that powers AI innovation across a global technology business, designing and building the infrastructure behind next-generation AI applications, optimising performance, ensuring reliability, and leading the strategy to make our AI platform world-class.
Working closely with Platform Engineering, DevOps, DevEx, and Cloud teams, you'll be our AI Platform ambassador, driving best practices, removing blockers, and enabling teams across the organisation to ship AI features faster and more reliably. This is a high-impact opportunity to solve complex challenges across AWS, Kubernetes, Amazon Bedrock, Agentic AI, and developer tooling, while influencing platform strategy, championing AI-powered ways of working, and leaving a lasting mark on the future of work.
Flexible, Hybrid Working
Some of Your Responsibilities & Core Duties will include:
- Own AI platform infrastructure: Design, build, and maintain AWS infrastructure, EKS clusters, and deployment pipelines for our AI applications using Terraform, GoCD, and infrastructure as code.
- Drive operational excellence: Monitor, troubleshoot, and optimize the performance of our AI platform, including Model Gateway, AI Agentic Gateway, Amazon Bedrock, and OpenSearch.
- Build and optimize CI/CD pipelines: Create smooth, frictionless deployment processes for AI applications; reduce deployment time and eliminate bottlenecks.
- Monitor and solve at scale: Use Kibana/Elasticsearch, DataDog, CloudWatch, and other observability tools to identify, diagnose, and resolve issues affecting AI applications.
- Lead platform strategy: Define and implement the roadmap to make our AI platform world-class, focusing on reliability, scalability, performance, and developer experience.
- Be the AI Platform ambassador: Work with Platform Engineering, DevOps, DevEx, and Cloud teams to adopt and influence best practices across the organization.
- Optimize costs and FinOps: Monitor and optimize infrastructure costs for AI workloads; implement cost allocation, budgeting, and efficiency improvements across AWS services.
- Champion AI-powered productivity: Expert use of AI tools (Claude, Claude Code, GitHub Copilot, Cursor) to accelerate delivery; evangelize AI tools across RG to maximize productivity, remove blockers, and solve defects faster.
- Develop platform tooling: Build internal tools, SDKs, and automation in Python to improve developer experience and enable teams to ship AI features independently.
- Ensure security and compliance: Partner with Security, Legal, and Data teams to implement governance, privacy, and compliance controls for AI infrastructure.
- Communicate and influence: Escalate issues quickly, push boundaries, and drive change across teams, influencing without authority to deliver results.
- Mentor and enable teams: Share knowledge, run training sessions, and document best practices to elevate AI platform capabilities across the organization.
The Experience and Key Skills you will have:
- Proven experience building and operating production infrastructure for AI or data-intensive applications at scale.
- Strong AWS expertise: Deep hands-on experience with AWS services, especially EKS (Kubernetes on AWS), Amazon Bedrock, OpenSearch, IAM, VPC, and core compute/storage services.
- Infrastructure as Code mastery: Expert in Terraform and infrastructure automation; experience with GoCD or similar CI/CD tools.
- Kubernetes and container orchestration: Strong kubectl skills and experience managing EKS clusters in production.
- Python development: Solid Python skills for building tooling, automation, and platform services.
- Observability and troubleshooting: Proficient with Kibana/Elasticsearch, DataDog, CloudWatch, and other monitoring/logging tools; able to diagnose complex production issues.
- AI-powered productivity champion: Expert using AI coding assistants (Claude, Claude Code, GitHub Copilot, Cursor) to accelerate work; passionate about evangelizing AI tools across teams.
- Platform and DevOps mindset: Experience working with Platform Engineering, DevOps, DevEx, and Cloud teams; able to adopt and influence best practices.
- Performance and cost optimization: Track record of improving system performance, reducing costs, and optimizing resource utilization; experience with FinOps practices and cloud cost management.
- Strong communication and influence: Able to escalate quickly, push boundaries, and drive change across teams without direct authority.
- Ownership and accountability: Takes end-to-end ownership from design through production, monitoring, and continuous improvement.
- Bonus: Experience with LLMs, RAG pipelines, vector databases, or Generative AI applications.
Your interview journey:
- Initial screening call with a member of our talent acquisition team
- 1st stage online interview with Director of AI Engineering and a member of the Platform Engineering team
- Final stage interview with Lead AI Engineer and a Platform Engineer.
We want every employee to feel comfortable bringing their passion, creativity, and individuality to work. We value all cultures, backgrounds, and experiences, because we believe diversity drives innovation and makes us stronger. Our approach to hiring and building teams is about more than filling roles - it’s about creating an environment where everyone can thrive, feel supported, and contribute to our mission of making the world a better place to work.