Responsibilities include but are not limited to:

Design and implement agentic AI workflows using UiPath and Salesforce Agentforce, combining LLMs, rules, APIs, and ML models for end‑to‑end automation.
Develop reusable agent frameworks and components to standardize and accelerate AI solution delivery.
Build, train, and deploy machine learning models (classification, regression, time‑series, anomaly detection) using DataRobot, leveraging Snowflake and Databricks for large‑scale data engineering.
Integrate ML models into enterprise workflows, APIs, and downstream applications.
Engineer integrations across enterprise systems using REST APIs, event-driven architectures, and robust data pipelines.
Support CI/CD and MLOps practices for scalable model deployment, monitoring, retraining, and lifecycle management.
Ensure compliance with AI governance and model risk policies, maintaining monitoring, documentation, and audit readiness.

Qualifications Required Skills:

Hands-on experience with agentic AI, orchestration, or intelligent automation platforms (UiPath strongly preferred).
Strong experience building and deploying ML models using DataRobot or comparable platforms.
Solid experience working with Snowflake and/or Databricks for data and ML workloads.
Proficiency in Python; experience with SQL and API-based integrations.
Strong understanding of ML lifecycle, model evaluation, and production deployment.
Exposure to LLMs, prompt engineering, RAG, and AI agents in enterprise environments.
Experience operating AI solutions in regulated industries (financial services, healthcare, etc.).
Familiarity with MLOps, feature stores, and model monitoring practices.

Preferred Skills:

Experience with Agentic AI and AI workflow orchestration.
Exposure to Generative AI (LLMs, prompt engineering, copilots, or AI assistants).
Experience building or supporting Intelligent Document Processing (IDP) solutions.
Knowledge of OCR, Computer Vision, and document classification/extraction techniques.
Familiarity with Machine Learning concepts, model integration, or ML platforms.
Experience integrating AI and automation solutions with enterprise platforms (e.g., CRM, ServiceNow, core banking systems).

Required Experience:

Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
Minimum of 6 years of experience building production-grade AI, ML, or automation solutions and AI Technology.

Preferred Experience:

Senior AI Engineer

Key skills