Description

Design and scale AI-driven solutions while leading technical enablement and adoption efforts across the enterprise.

Responsibilities

• Architect end-to-end AI/ML systems, including data pipelines, model development, and production monitoring.
• Define architecture standards, governance frameworks, and best practices to ensure scalability and security.
• Translate business requirements into technical AI solutions by collaborating with engineering, data science, and product teams.
• Lead technical mentorship and guide teams through AI adoption, education, and instructional rollout.
• Evaluate and select appropriate models, frameworks, and cloud tools based on specific use cases and constraints.

Required Skills

• 7+ years of experience in software engineering, data engineering, or solutions architecture.
• Proven track record of designing and deploying machine learning or AI solutions in production.
• Strong proficiency in Python, Java, or Scala.
• Hands-on experience with TensorFlow, PyTorch, scikit-learn, or Hugging Face.
• Solid understanding of data architecture, APIs, microservices, and distributed systems.
• Experience with MLOps practices, including CI/CD for ML, model versioning, and governance.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

Preferred Skills

• Cloud experience with AWS (SageMaker, Bedrock, Lambda) or Azure/GCP.
• Experience delivering AI training sessions, workshops, or internal learning programs.
• Familiarity with generative AI, LLMs, prompt engineering, and AI orchestration patterns.

Key Skills

Education

Any Graduate