Description

 Required

 

• Python or another production programming language: 4+ years.
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
• SQL and experience with structured and unstructured data.
• Git and software development lifecycle practices.
• REST APIs, cloud services, and automated testing.
• Experience with solution design, system integration, and technical documentation. 
  
   

Preferred

 

• Experience with generative AI, large language models, prompt engineering, or retrieval-augmented generation.
• Knowledge of blockchain, IoT, or other emerging technologies.
• Experience with Docker, Kubernetes, and CI/CD tools.
• Familiarity with vector databases, model monitoring, and MLOps platforms. 
  
   

Overall Responsibilities

 

• Lead the design, development, and delivery of AI and emerging-technology projects.
• Assess new technologies and recommend solutions that improve business processes.
• Develop scalable, secure, and maintainable AI applications.
• Define technical approaches, architecture, delivery plans, and quality standards.
• Mentor team members through code reviews, technical guidance, and knowledge sharing.
• Collaborate with Product, Engineering, Operations, and other stakeholders.
• Track project risks, dependencies, quality, and delivery progress.
• Ensure solutions support business objectives, security requirements, and responsible AI practices. 
  
   

Technical Skills (By Category)

Programming Languages

 

• Essential: Python and strong software development practices.
• Preferred: Java, JavaScript/TypeScript, or another programming language. 
  
   

Databases and Data Management

 

• Essential: SQL, data preparation, data quality, and experience with structured and unstructured data.
• Preferred: NoSQL, vector databases, data pipelines, and model data management. 
  
   

Cloud Technologies

 

• Essential: Experience deploying applications or AI services using a major cloud platform.
• Preferred: Serverless services, Kubernetes, Docker, and cloud-based AI platforms. 
  
   

Frameworks and Libraries

 

• Essential: At least one AI/ML framework, such as PyTorch, TensorFlow, or Scikit-learn.
• Preferred: Generative AI frameworks, model-serving tools, MLOps platforms, and API frameworks. 
  
   

Development Tools and Methodologies

 

• Essential: Git, Agile delivery, CI/CD, code reviews, automated testing, and software architecture.
• Preferred: Infrastructure as code, model monitoring, experiment tracking, and automated deployment. 
  
   

Security Protocols

 

• Essential: Secure coding, access controls, encryption, secrets management, data protection, and responsible AI principles.
• Preferred: Threat modeling, privacy-preserving AI, model security, and compliance controls. 
  
   

Experience Requirements

 

• 5+ years of experience in software development, AI engineering, or technology delivery.
• Experience leading or contributing to projects using AI or other emerging technologies.
• Experience designing software architectures and applying appropriate design patterns.
• Experience mentoring team members and coordinating cross-functional delivery.
• Experience communicating technical recommendations to non-technical stakeholders.
• Experience in financial services, technology, healthcare, or other regulated industries is preferred.
• Equivalent practical experience, technical training, or a portfolio of relevant projects may be considered. 
  
   

Day-to-Day Activities

 

• Design, develop, test, and deploy AI-enabled solutions.
• Review requirements, technical designs, data sources, and delivery priorities.
• Evaluate new technologies through research, prototypes, and proof-of-concept work.
• Lead technical discussions, code reviews, and solution evaluations.
• Support team members through mentoring and problem-solving.
• Meet with Product, Engineering, and business stakeholders to confirm requirements and progress.
• Monitor project risks, quality, timelines, and technical dependencies.
• Document architecture, implementation decisions, test results, and operating procedures.
• Make technical recommendations within agreed architecture, security, and delivery standards. 
  
   

Qualifications

 

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.
• Relevant AI, cloud, data, or emerging-technology certifications are preferred.
• Complete Synechron training on security, data protection, responsible AI, and delivery standards.
• Maintain current knowledge of AI, software architecture, cloud technologies, data practices, and industry developments

Key Skills

Education

Bachelor's or Master's degrees