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AI Engineer
Skills
Computer ScienceDevopsAgility TrainingAmazon Web ServicesContextCreativeDatabases
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor's or Master's degree in Computer Science IT or related field
- Certification in at least one Cloud or AI-related area
- 9+ years in New Product Development
- 3+ years as an AI Engineer using LLMs and AI-driven products
- Strong experience delivering complex technical products at scale
- Proficiency in LLMs AWS Python Java Spring Boot Node.js Angular Microservices TypeScript and JavaScript
- Experience with REST SOAP APIs databases MongoDB PostgreSQL and Redis
- Familiarity with containerization DevOps and cloud platforms AWS Azure
- Experience with Gen AI technologies including Agentic AI LLMs LangChain and Semantic Kernel
- Knowledge of authentication standards OAuth2 JWT and SAML
- Strong communication interpersonal and stakeholder collaboration skills
- Ability to manage multiple priorities in a fast-paced environment
- Experience with MLOps or LLMOps and deploying machine learning pipelines
- Deep knowledge of Docker and orchestration concepts
Nice to have
- Proactive ownership
- Analytical mindset
- Strategic communication
- Innovative problem solving
- Collaborative leadership
- Agility in global teams
- Trustworthy AI focus
- Passion for learning
Day to day
- Design and develop enterprise-grade AI/ML and Generative AI solutions using modern cloud-native architectures.
- Build and deploy custom AI agents, LLM-based workflows, RAG pipelines, and semantic search assistants for business use cases.
- Maintain, monitor, and optimize scalable AI systems with strong focus on performance, reliability, cost-efficiency, and responsible AI practices.