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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in leading AI software engineering teams, with a strong focus on machine learning model production, cloud deployment, and AI process optimization. Proficient in managing technical quality, mentoring engineers, and driving AI adoption within regulated environments.
Highest-signal resume keywords
Machine Learning Model ProductionStrong PythonCloud AI Services (AWS Preferred)DevOps and IT AutomationAI Process Optimization
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningLarge Language ModelsGenerative AIAPIs DevelopmentRetrieval Augmented GenerationVector SearchCI/CD PipelinesPrompt EngineeringData ProtectionModel Evaluation
Soft Skills
MentoringTechnical DirectionCommunication
Tools & Technologies
DockerPyTorchTensorFlowCloud DeploymentMonitoring Tools
Industry Keywords
Financial ServicesRegulated EnvironmentAI AdoptionData ClassificationAudit Trails
Tech Stack
Tools & technologiesAWSCloudDockerMicroservicesPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Lead AI software engineers and AI process optimisation specialists
- Provide technical direction, ensure code quality, conduct craft-focused one-to-ones and develop engineers
- Own the technical quality of shipped work and provide technical input to performance reviews
- Analyse IT and business workflows to identify valuable AI productivity opportunities
- Establish signed process baselines before builds and report measured outcomes afterward
- Deliver AI systems from design through production support
- Maintain risk classifications, data classifications, evaluation sets, shadow-run results and audit trails
- Prioritise, size and sequence the business-wide AI delivery backlog
- Enforce data-layer permissions, centralized model access and audit logging
- Lead architecture and security reviews early in the design process
- Own runbooks, monitoring, on-call participation and post-incident follow-through
- Own the internal AI platform, including prompt libraries, evaluation harnesses, reusable agents and shared components
- Evaluate models, tools and vendors using benchmarks, cost, failure modes and data handling
- Track live system running costs and retire systems whose benefits no longer exceed costs
- Plan team capacity and produce the annual hiring proposal
- Propose improvements to AI adoption, standardization and delivery frameworks
- Serve as the technical point of contact between the AI function and IT
- Mentor engineers and colleagues across the company in effective AI use
- Report to the Chief AI Officer, with the Chief Technology Officer as functional owner
Requirements
What you’ll need- 6+ years experience building software or data systems
- 2+ years leading engineers as a manager or technical lead
- Production experience with machine learning models, large language models or generative AI solving actual business problems
- Strong Python
- Production experience building services and APIs, orchestrating agents and tool use, and working with major model providers
- Production experience with retrieval augmented generation and vector search
- Experience with Docker, cloud deployment and CI/CD pipelines
- Evaluation discipline covering regression, latency, cost, accuracy, hallucination and model drift
- Practical command of retrieval, agents, tool use and prompt engineering
- Clear understanding of when fine tuning is appropriate
- DevOps and IT automation experience, including CI/CD integration, infrastructure automation and workflow tooling
- Experience with REST APIs and AI-driven microservices
- Experience with cloud AI and ML services; AWS preferred
- Command of token and inference cost models at pilot and full-adoption scale
- Data protection experience in a regulated environment
- Ability to explain AI limitations and risks to decision makers
- Experience evidencing business benefit against agreed baselines
- Comfortable working across a dual reporting line
- Applicants must be eligible or have legal authorization to work in Cyprus
- Resumes must be submitted in English
- Financial services or another regulated industry is advantageous
- Experience training models with PyTorch or TensorFlow is advantageous, not required
Benefits
Comp & perks- Hybrid Work Model (2 days working from home)
- Comprehensive Health plan starting from the first day of employment
- Pension plan
- 13th salary payment
- Additional Paid Annual Leave (up to 30 days, based on years of service)
- Up to 5 Carry over annual leave days from previous year to the next one
- Birthday Leave
- Udemy Business access
- Monthly Wolt Vouchers
- Monthly meals & treats at the office
- Participation in company's Group Discount Scheme
- Gym Membership
- Referral Bonus Program
- Summer Short Fridays (August)
- Visa Sponsorship and Relocation Assistance (If applicable)