Senior Al Engineer

Job description

Description & Requirements

Position Summary

The Senior AI Engineer with GenAI expertise is responsible for developing advanced technical solutions, integrating cutting‑edge generative AI technologies.

This role requires a deep understanding of modern technical and cloud‑native practices, AI, DevOps, and machine learning technologies, particularly in generative models.

You will support a wide range of customers through the “Ideation to MVP” journey, showcasing leadership and decision‑making abilities while tackling complex challenges.

Key Responsibilities

Technical & Engineering Leadership

• Develop solutions leveraging GenAI technologies, integrating advanced AI capabilities into cloud‑native architectures to enhance system functionality and scalability.
  
  
• Lead the design and implementation of GenAI‑driven applications, ensuring seamless integration with microservices and container‑based environments.
  
  
• Create solutions that fully leverage the capabilities of modern microservice and container‑based environments running in public, private, and hybrid clouds.
  
  
• Contribute to leadership across the Cloud Native domain with an expert understanding of open‑source technologies (e.g., Kubernetes/CNCF) and partner technologies.
  
  
• Collaborate on joint technical projects with partners, including Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell/VMware.
  
  

Service Delivery

• Engineer innovative GenAI solutions from ideation to MVP, ensuring high performance and reliability within cloud‑native frameworks.
  
  
• Optimize AI models for deployment in cloud environments, balancing efficiency and effectiveness to meet client requirements and industry standards.
  
  
• Assess existing complex solutions and recommend appropriate technical treatments to transform applications with cloud‑native/12‑factor characteristics.
  
  
• Refactor existing solutions to implement a microservices‑based architecture.
  
  

Innovation & Initiative

• Drive the adoption of cutting‑edge GenAI technologies within cloud‑native projects, spearheading initiatives that push the boundaries of AI integration in cloud services.
  
  
• Engage in technical innovation and support position as an industry leader.
  
  
• Author whitepapers, blogs, and speak at industry events.
  
  
• Maintain hands‑on technical credibility, stay ahead of industry trends, and mentor others.
  
  

Client Relationships

• Provide expert guidance to clients on incorporating GenAI and machine learning into their cloud‑native systems, ensuring best practices and strategic alignment with business goals.
  
  
• Conduct workshops and briefings to educate clients on the benefits and applications of GenAI, establishing strong, trust‑based relationships.
  
  
• Perform a trusted advisor role, contributing to technical projects (PoCs and MVPs) with a strong focus on technical excellence and on‑time delivery.
  
  

Mandatory Skills & Experience

• A passionate developer with 10+ years of experience in Java, Python, Node.js, and Spring programming, comfortable working as part of a paired/balanced team.
  
  
• Extensive experience in software development, with significant exposure to AI/ML technologies.
  
  
• Expertise in GenAI frameworks: Proficient in using GenAI frameworks and libraries such as LangChain, OpenAI API, Gemini, and Hugging Face Transformers.
  
  
• Prompt engineering: Experience in designing and optimizing prompts for various AI models to achieve desired outputs and improve model performance.
  
  
• Strong understanding of NLP techniques and tools, including tokenization, embeddings, transformers, and language models.
  
  
• Proven experience developing complex solutions that leverage cloud‑native technologies—featuring container‑based, microservices‑based approaches; based on applying 12‑factor principles to application‑engineering.
  
  
• Exemplary verbal and written communication skills (English).
  
  
• Positive and solution‑oriented mindset.
  
  
• Solid experience delivering Agile and Scrum projects in a Jira‑based project management environment.
  
  
• Proven leadership skills and the ability to inspire and manage teams.
  
  

Desired Skills & Experience

• Machine Learning Operations (MLOps): Experience in deploying, monitoring, and maintaining AI models in production environments using MLOps practices.
  
  
• Data engineering for AI: Skilled in data preprocessing, feature engineering, and creating pipelines to feed AI models with high‑quality data.
  
  
• AI model fine‑tuning: Proficiency in fine‑tuning pre‑trained models on specific datasets to improve performance for specialized tasks.
  
  
• AI ethics and bias mitigation: Knowledgeable about ethical considerations in AI and experienced in implementing strategies to mitigate bias in AI models.
  
  
• Knowledgeable about vector databases, LLMs, and SMLs, and integrating with such models.
  
  
• Proficient with Kubernetes and other cloud‑native technologies, including experience with commercial Kubernetes distributions (e.g., Red Hat OpenShift, VMware Tanzu, Google Anthos, Azure AKS, Amazon EKS, Google GKE).
  
  
• Deep understanding of core practices including DevOps, SRE, Agile, Scrum, XP, Domain‑Driven Design, and familiarity with the CNCF open‑source community.
  
  
• Recognized with multiple cloud and technical certifications at a professional level, ideally including AI/ML specializations from providers like Google, Microsoft, AWS, Linux Foundation, IBM, or Red Hat.
  
  

Verifiable Certification

• At least one recognized cloud professional / developer certification (AWS/Google/Microsoft)

Required Skill Profession

It & Technology