AI - Technical Lead

AI - Technical Lead

We are looking for an AI Lead for our team of Data Scientists. This role will focus on leading the development, deployment, and monitoring of AI and machine learning solutions, including Generative AI (GenAI) technologies such as chatbots. The ideal candidate will have experience working in an onshore-offshore model, with a strong background in AI/ML development and operational best practices. This role requires close collaboration with the onshore AI Manager and cross-functional teams including AI Ops, ML Engineering, and Data Engineering.

Qualifications Skills

Education:

Bachelor s or Master s degree in Computer Science, Data Science, AI, or a related field.

Certifications in cloud platforms (Azure, AWS, GCP) or MLOps frameworks are a plus.

Experience:

5 years of experience in Data Science, with 2+ years of experience leading AI/ML development and operations in onshore/offshore model.

Hands-on experience with deploying AI models, including LLMs and GenAI solutions.

Experience working with cloud AI platforms (Azure AI, AWS SageMaker, Google Vertex AI).

Technical Skills:

Proficient in Python and SQL

Familiarity with MLOps tools like MLflow, Kubeflow, or Airflow.

Experience with monitoring tools (Prometheus, Grafana) for AI performance.

Knowledge of containerization and orchestration tools (Docker, Kubernetes).

Proficiency in scripting languages like Python or Bash.

Understanding of CI/CD pipelines (Jenkins, GitHub Actions) for model deployment.

Key Responsibilities

AI Model Development Deployment:

Lead the offshore team in building, deploying, and managing AI/ML models, including traditional machine learning and GenAI solutions (e.g., LLMs, RAG systems).

Collaborate with AI Engineers to integrate models into enterprise applications and workflows.

Support the implementation of CI/CD pipelines for efficient model deployment and scaling.

Monitoring Performance Optimization:

Develop monitoring systems to track model performance, latency, and drift.

Implement feedback loops for continuous model improvement in collaboration with data scientists.

Monitor GenAI outputs for issues like bias, hallucinations, and security vulnerabilities.

MLOps Automation Best Practices:

Establish MLOps practices to support continuous integration and deployment of AI models.

Automate model retraining, versioning, and rollback strategies.

Collaborate with AI Ops and Data Engineers to ensure smooth data and model pipelines.

Security Compliance:

Implement security measures to safeguard AI systems from data leaks, prompt injections, and unauthorized access.

Ensure AI solutions comply with relevant privacy and regulatory standards (e.g., HIPAA, GDPR).

Regularly audit AI pipelines for ethical practices and data governance.

Collaboration Communication:

Work closely with the onshore AI Manager and cross-functional teams to align AI initiatives with business goals.

Facilitate effective communication between onshore and offshore teams.

Contribute to documentation, playbooks, and best practices for AI operations.

Team Leadership Development:

Manage and mentor a team of data scientists, fostering professional growth and collaboration.

Encourage an innovative, problem-solving culture within the team.

Soft Skills:

Strong problem-solving abilities and a proactive approach to troubleshooting.

Excellent collaboration skills with cross-functional teams.

Results-driven mindset with a focus on operational efficiency and scalability.

Ability to thrive in a fast-paced, dynamic environment.