AI Enabled Automation Engineer

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Job Description

Title

AI Enabled Automation

Type of Employment

Permanent

Overall Years of Experience

• 0- 2 years

Relevant Years of Experience

• 1 years

We are looking to hire people with strong Power Platform skills and who are interested in learning new technologies in the process automation space – RPA, AI/ML, Cognitive, Conversational Chat, Gen AI.

Position Summary

• Requires 0-2 years minimum prior relevant experience.
• Build and deliver priority Finance AI use cases across Overheads, FSS, and Controllership.
• Design end-to-end agentic workflows for data extraction, case assembly, validation, recommendations, report generation, workflow triggering, exception review, and monitoring
• Build multi-agent or orchestrated AI workflows using LLMs, tools, retrieval, rule engines, and workflow services.
• Engineer prompts, context handling, tool invocation, memory/retrieval patterns, structured outputs, and response guardrails.
• Select the right pattern for each problem, including deterministic workflows, agentic orchestration, extraction/classification, matching/recommendation, summarization, and commentary generation.
• Implement evaluations, offline test sets, regression packs, confidence thresholds, and feedback loops to improve solution quality.
• Integrate with enterprise systems and data sources such as Oracle / Fusion, PBCS / EPM, CRM / Salesforce, bank statements, ticketing or workflow systems,
• Email / Teams, and manual structured or semi-structured inputs.
• Build data preparation, normalization, case assembly, schedule preparation, and output packaging pipelines required for Finance operations use cases
• Design RBAC-aware workflows, approval routing, SLA and escalation logic, monitoring, and exception queues.
• Implement clear human-in-the-loop controls for high-risk actions; AI should recommend or prepare, while business users approve where required.
• Build reusable components across use cases, including source extractors, validation agents, case assembly services, recommendation packaging, and report generation patterns.
• Work closely with Finance SMEs, product owners, enterprise architecture, security, and engineering teams to convert business problems into production-ready solutions.
• Document solution architecture, prompt packs, rule packs, API specifications, operating procedures, and support runbooks.
• Strong Python and SQL skills, with ability to build production-grade services, data pipelines, and workflow logic.
• Experience building GenAI or agentic applications with enterprise integrations, tool calling, structured outputs, and workflow orchestration.
• Basic AI concepts using AI builder and Co-Pilot.
• Knowledge on Dataverse and it’s concepts around security and automation.
• Database knowledge of any 1 RDBMS product (SQL, Oracle, etc.).
• Experience in developing solutions using a combination of automation technologies like, AI/ML, RPA.
• Deep knowledge and experience in Agile methodologies
• Excellent written and verbal communication skills. Ability to write clear, understandable logic for maintainable code, which meets design specifications.

Qualifications

• A bachelor's or master's degree in computer science
• Excellent communication skills with consulting experience preferred

Roles and Responsibilities

Essential

• Experience with integration of data from multiple data sources like Azure SQL, SQL Server, SAP, Service Now etc.
• Integrate AI-driven features like Copilot to augment solution capabilities and deliver intelligent business insights.
• Collaborate with cross-functional teams to gather requirements and translate them into scalable, efficient technical solutions.
• Ensure the solutions meet performance, scalability, and security requirements.
• Lead the technical team as part of project delivery, provide mentorship and technical guidance to team members.
• Understand and analyse business requirements by working with various stakeholders and create the appropriate information architecture and solution approach.
  Understand and analyse user requests. Take full responsibility for the complete lifecycle of an application from analysis to final deployment.

Roles and Responsibilities

Skills and attributes for success

• Experience in software engineering, data engineering, AI engineering, or related roles, with meaningful hands-on experience in GenAI / LLM solutions.
• Strong Python and SQL skills, with ability to build production-grade services, data pipelines, and workflow logic.
• Experience building GenAI or agentic applications with enterprise integrations, tool calling, structured outputs, and workflow orchestration.
• Experience with extraction pipelines, document understanding, retrieval / knowledge grounding, rules engines, matching or recommendation logic, and evaluation frameworks.
• Good understanding of system integration patterns, REST APIs, authentication, monitoring, exception handling, and production operations.
• Working understanding of Finance processes such as month-end close, AP, AR, OTC, RTR, PTP, reconciliations, journal handling, approvals, and controls.
• Experience designing explainable and auditable AI outputs for business-critical workflows.
  

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