Senior Engineer - AI

JOB SUMMARY -

The Senior Engineer - AI is responsible for end-to-end AI projects from problem definition to model to deployment and monitoring. The primary focus of this role is to combine expertise in machine learning, data engineering, and system architecture to deliver complex AI solutions. This position requires a deep understanding of AI principles, strong problem-solving skills, and the ability to effectively communicate with both technical and non-technical stakeholders.

MINIMUM REQUIREMENTS -

• 3+ years of experience in AI/ML development, with a proven track record of production-level deployments.
• Expert in Python and familiar with core ML/DL frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers)
• Design and implement integrations using Model Context Protocol to connect AI models with external tools, APIs, and data sources.
• Strong experience developing AI-driven workflows using eknowledge platforms, and AI agent frameworks such as Microsoft Copilot, Glean, and Google Agentspace
• Solid understanding of ML theory, statistics, linear algebra, optimization, and deep learning architectures.
• Experience with cloud services (AWS, GCP, Azure), containerization (Docker, Kubernetes), and MLOps tools (MLflow, DVC, Airflow).
• Familiarity with tools for model explainability (SHAP, LIME), monitoring, and continuous retraining.
• Possesses and applies simple to moderate knowledge of particular product or platform to the completion of assignments
• Ability to learn, understand and adopt new software platforms and processes
• 3+ years experience using Jira, Bitbucket and Confluence agile toolsets or similar
• High proficiency in Microsoft Office suite products
• Good communication skills and ability to communicate at some levels of the organization (technical and business)
• 3+ years experience with IT ticketing software (Quality Center, ServiceNow, JIRA)
• 3+ years experience using Jira, Bitbucket and Confluence agile toolsets or similar
• 3+ years experience working with small, geographically distributed teams
• 3+ years experience working both independently and in a team oriented, collaborative environment
• 3+ years experience in agile/waterfall software delivery methodologies
• Ability to be flexible while delivering assignments with understanding that deliverables may change based on business needs

EDUCATION REQUIREMENTS -

• Bachelor's degree or foreign equivalent in computer science, engineering or related field or equivalent work experience

Principal Duties and Responsibilities -

• Problem & solution design
  • Work with stakeholders to frame business problems as AI/ML use cases
  • Define success metrics, constraints, and data requirements
• Data engineering & preparation
  • Ingest, clean, and transform data from multiple sources
  • Build and maintain feature pipelines / datasets for training and inference
• Model development
  • Select appropriate algorithms (ML, deep learning, NLP, recommendation, etc.)
  • Train, tune, and validate models using best practices (cross‑validation, baselines, ablation, etc.)
• Evaluation & experimentation
  • Design experiments (A/B tests, offline metrics) to compare models and approaches
  • Analyze results and iterate quickly to improve performance and robustness
• MLOps & deployment
  • Package and deploy models to production (APIs, batch jobs, streaming)
  • Implement CI/CD for ML, versioning of data/models, and reproducible training
• Monitoring & maintenance
  • Set up monitoring for drift, performance, latency, cost, and failures
  • Retrain, recalibrate, or roll back models as data and business conditions change
• Keeps abreast of improvements in software techniques and develop some improvements on own
• Ability to be flexible while delivering assignments with understanding that deliverables may change based on business needs

ADDITIONAL CHARACTERISTICS -

• Independently performs assignments to achieve stated objective. Determines and develops approach to solutions
• Receives technical guidance only on unusual or complex problems or issues
• May be responsible for entire projects having moderate to complex scope/impact or portions of projects having considerable scope/impact
• Uses judgment and discretion to determine work priorities, receiving little instruction from others