Workday Developer

• Workday Developer (Contract/FTE)
• Rel. Exp (Years): 5 Years+
• Location: Pan India
• Any Project specific Prerequisite skills: Workday Developer

Responsibilities:

• Develop and maintain Integrations between Workday and external systems using Workday Workday Studio, Extend, and other tools.
• Develop and deploy additional functionality within Workday utilizing Workday Extend.
• Engage and collaborate with a range of stakeholders to gather requirements.
• Develop documentation for newly created Applications, including user guides, specifications and procedures.
• Support internal teams to use newly implemented functionality with some knowledge transfer and training.
• Support & Develop integrations of various types such as third-party payroll, PECI/PICOF, API calls, Connectors, EIBs and Studios, third-party internal and external systems like Ceridian.
• Strong configuration in Workday business processes, Custom reports, EIB Inbounds, Security, Alerts and Notifications related to Integrations.
• Discover, Design and Develop new Integrations and report requests through the Jira queue.
• Ownership and accountability of both Quality and RUN responsibilities about all workday-related projects.
• Troubleshoot and fix production issues and help prioritize against existing backlog based on severity and impact.
• Be able to easily put on your business analyst hat if needed and advise business for the best workday practice.

Experience:

• 5+ Years of experience with HR Technology
• 3+ years of hands-on experience in building and supporting Workday Integrations with strong knowledge on connectors (Core connectors, Packaged connectors, PECI/PICOF, WECI), EIBs, Custom Reports, BIRT, document transformation and Studio
• 3+ years of strong hands-on experience in Workday HCM functional configuration setup, Security configuration, EIB Inbounds, Business Processes, Alerts and Notifications framework, and building dashboards
• 1+ years of experience in developing integration in Workday Extend and Orchestration preferred
• Strong experience in Workday Studio, SOAP API, REST API, and Import API patterns
• Excellent verbal, written, communication, interpersonal, and presentation skills with proven business analyst skills
• Passion for Workday technology, and industry automation and enjoys solving business problems

Nice to have:

Experience with Payroll Integration and DCOD AI, and AI agents-are fair, transparent, accountable, secure, and aligned with Chevron's ethical principles. Working at the intersection of AI/ML engineering, ethics, and policy, you will build and maintain the automation, scripts, and tooling that power Chevron's AI impact assessment process, and help operationalize Responsible AI controls within our AI governance platform (Credo AI). You will collaborate closely with our Cybersecurity, Legal, and Data Privacy teams to ensure that AI solutions, vendors, and internal use cases adhere to Chevron guidelines, policies, and emerging regulations.

Responsibilities for this position may include but are not limited to:

Build, maintain, and enhance the automation flows, scripts, and tooling that support Chevron's AI impact assessment and Responsible AI review processes.
Configure and administer Chevron's AI governance platform (Credo AI)-adding risk scenarios, controls, and review workflows that enable teams to document mitigations, provide evidence, and track AI risks across the lifecycle.
Design and operate review and approval checkpoints, including pre-production questionnaires and periodic re-reviews of AI use cases, streamlining through automation where possible.
Establish and run model review processes for both pre-trained/foundation models and custom-built machine learning models.
Assist in AI Discovery and maintain an inventory of AI models, agents, and use cases across the enterprise, ensuring proper documentation and lifecycle governance.
Conduct ethical risk assessments and impact analyses for AI use cases, including alignment with regulations such as the EU AI Act and industry frameworks such as the IOGP Responsible Use of AI principles, and NIST AI Risk Management Framework.
Evaluate AI vendors, models, and external AI access requests for fairness, security, and policy compliance, partnering with Cybersecurity, Legal, and Data Privacy.
Influence the development and adoption of tools and methodologies to detect and mitigate bias, drift, and unintended consequences in machine learning and generative AI systems.
Lead training, FAQs, and awareness campaigns-leveraging Teams and Copilot-to promote ethical AI practices and communicate process changes across business units.
Partner with cross-functional teams to integrate Responsible AI principles into product development and deployment workflows.
Required Qualifications

Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
Minimum 3-7 years of professional experience in data science, analytics, or AI/ML engineering roles.
Proficiency in Python and experience building automation, scripts, or data pipelines that integrate with enterprise platforms and APIs.
Demonstrated ability to reason through ethical implications of AI systems and articulate trade-offs.
Experience working with interdisciplinary teams (e.g., cybersecurity, legal, privacy, policy) to embed Responsible AI principles.
Strong communication and presentation skills to convey complex technical concepts to diverse audiences.
Familiarity with data governance frameworks and enterprise compliance standards (e.g., GDPR, CCPA, NIST, OECD).
Preferred Qualifications

Master's degree in Data Science, Computer Science, or a related field.
Certifications in Responsible AI, Data/AI Ethics, Cybersecurity, or AI Governance.
Experience developing and evaluating machine learning models using Python and libraries such as scikit-learn, TensorFlow, or PyTorch.
Experience with generative AI or agentic AI frameworks, tools, or applications, and with governing AI agents (e.g., agent registries, Microsoft Agents 365).
Experience with AI governance or model-risk platforms (e.g., Credo AI) and workflow automation (e.g., Power Automate, Azure DevOps).
Knowledge of fairness, interpretability, and robustness techniques in AI.
Experience with enterprise AI platforms (e.g., Azure ML / Azure AI Foundry, Databricks, DataRobot).
Familiarity with emerging AI regulations and industry frameworks (e.g., EU AI Act, NIST AI Risk Management Framework, IOGP Responsible Use of AI).
Proven ability to work autonomously in ambiguous environments and make connections between disparate data