Custom Software Engineer
Bengaluru
Job No. atci-5212034-s1924799
Full-time
工作描述
Project Role : Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : SAP Build Process Automation
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary
Design and deliver AI native, autonomous business process solutions using SAP Build Process Automation by combining deep workflow, rules, and automation expertise with agentic AI patterns (LLMs + tools + retrieval + evaluation). This role focuses on moving from rule based automation to intelligent, decision aware, self optimizing processes that can interpret context, recommend actions, and execute workflows safely at enterprise scale—without training foundation models from scratch.
Core Responsibilities
1) Intelligent Process Automation Design
Design, build, and deploy end to end business process automations using workflows, business rules, and automation components.
Model human in the loop and straight through processes aligned to enterprise policies, controls, and audit requirements.
Translate business requirements into scalable, maintainable automation artifacts.
2) Workflow, Rules & Decision Orchestration
Build workflows that orchestrate tasks, approvals, integrations, and system interactions across SAP and non SAP landscapes.
Implement decision logic using business rules and decision tables with clear traceability and version control.
Design reusable automation components to reduce duplication and accelerate delivery.
3) Integration Aware Automation
Integrate automated processes with enterprise systems via APIs, events, and service calls.
Coordinate process execution with backend services, integrations, and data platforms to enable end to end automation.
Handle error scenarios, compensating actions, and retries to ensure reliable execution.
4) AI Native Process Intelligence (Agentic Automation Layer)
Build process agents that can:
o Interpret unstructured or semi structured inputs (requests, descriptions, exceptions).
o Recommend next steps or generate workflow paths dynamically within approved boundaries.
o Trigger tools and system actions through controlled, auditable interfaces.
Implement retrieval grounded decision support by pulling from process documentation, policies, historical cases, and outcomes—ensuring AI outputs are explainable and verifiable.
Enable conversational process interactions (e.g., start a request , why is this stuck , what s the best next step ) with clear confirmations and guardrails.
5) Quality Engineering & Evaluation Loops
Define automated testing strategies for workflows, rules, and integrations (happy paths, edge cases, and failure modes).
Establish evaluation harnesses for AI behavior: scenario simulations, golden decision sets, and outcome accuracy checks.
Gate releases of automation logic and AI prompts/tools using measurable quality thresholds.
6) Observability, Monitoring & Continuous Optimization
Monitor process execution, SLAs, bottlenecks, and exception patterns.
Use AI augmented insights to identify inefficiencies, recurring failures, and optimization opportunities.
Continuously refine workflows, rules, and AI prompts based on real execution data and feedback.
7) Governance, Security & Responsible AI
Enforce role based access, approvals, and segregation of duties within automated processes.
Implement responsible AI guardrails: action boundaries, data minimization, explainability, and audit logs.
Ensure compliance with enterprise risk, control, and regulatory requirements.
8) Automation Strategy & Enablement
Support automation roadmaps and identify candidates for intelligent automation and autonomy.
Collaborate with business, IT, integration, and data teams to scale automation adoption.
Create standards, templates, and playbooks to enable consistent delivery across teams.
Primary Skills (AI Native Must Have)
Strong hands on expertise in SAP Build Process Automation (workflows, rules, and automation design).
Solid understanding of business process modeling, orchestration, and exception handling.
Experience integrating automated processes with enterprise systems and APIs.
AI native capability: agentic workflows, retrieval grounded decisions, evaluation loops, and safe automation boundaries.
Secondary / Strongly Beneficial Skills
Business process analysis and optimization experience.
Exposure to low code/no code development paradigms at enterprise scale.
Familiarity with integration platforms and event driven architectures.
Strong documentation and change management practices for automated processes.
What This Role Does Not Center On
Training or fine tuning foundation AI models.
Simple task automation without governance, observability, or intelligence.
Value Delivered
Faster process delivery through reusable, intelligent automation patterns.
Higher efficiency and better outcomes via AI guided decisioning and dynamic workflows.
Scalable, compliant automation foundations that enable the transition from automation to autonomy.
Additional Information
A 15 years full time education is required
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : SAP Build Process Automation
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary
Design and deliver AI native, autonomous business process solutions using SAP Build Process Automation by combining deep workflow, rules, and automation expertise with agentic AI patterns (LLMs + tools + retrieval + evaluation). This role focuses on moving from rule based automation to intelligent, decision aware, self optimizing processes that can interpret context, recommend actions, and execute workflows safely at enterprise scale—without training foundation models from scratch.
Core Responsibilities
1) Intelligent Process Automation Design
Design, build, and deploy end to end business process automations using workflows, business rules, and automation components.
Model human in the loop and straight through processes aligned to enterprise policies, controls, and audit requirements.
Translate business requirements into scalable, maintainable automation artifacts.
2) Workflow, Rules & Decision Orchestration
Build workflows that orchestrate tasks, approvals, integrations, and system interactions across SAP and non SAP landscapes.
Implement decision logic using business rules and decision tables with clear traceability and version control.
Design reusable automation components to reduce duplication and accelerate delivery.
3) Integration Aware Automation
Integrate automated processes with enterprise systems via APIs, events, and service calls.
Coordinate process execution with backend services, integrations, and data platforms to enable end to end automation.
Handle error scenarios, compensating actions, and retries to ensure reliable execution.
4) AI Native Process Intelligence (Agentic Automation Layer)
Build process agents that can:
o Interpret unstructured or semi structured inputs (requests, descriptions, exceptions).
o Recommend next steps or generate workflow paths dynamically within approved boundaries.
o Trigger tools and system actions through controlled, auditable interfaces.
Implement retrieval grounded decision support by pulling from process documentation, policies, historical cases, and outcomes—ensuring AI outputs are explainable and verifiable.
Enable conversational process interactions (e.g., start a request , why is this stuck , what s the best next step ) with clear confirmations and guardrails.
5) Quality Engineering & Evaluation Loops
Define automated testing strategies for workflows, rules, and integrations (happy paths, edge cases, and failure modes).
Establish evaluation harnesses for AI behavior: scenario simulations, golden decision sets, and outcome accuracy checks.
Gate releases of automation logic and AI prompts/tools using measurable quality thresholds.
6) Observability, Monitoring & Continuous Optimization
Monitor process execution, SLAs, bottlenecks, and exception patterns.
Use AI augmented insights to identify inefficiencies, recurring failures, and optimization opportunities.
Continuously refine workflows, rules, and AI prompts based on real execution data and feedback.
7) Governance, Security & Responsible AI
Enforce role based access, approvals, and segregation of duties within automated processes.
Implement responsible AI guardrails: action boundaries, data minimization, explainability, and audit logs.
Ensure compliance with enterprise risk, control, and regulatory requirements.
8) Automation Strategy & Enablement
Support automation roadmaps and identify candidates for intelligent automation and autonomy.
Collaborate with business, IT, integration, and data teams to scale automation adoption.
Create standards, templates, and playbooks to enable consistent delivery across teams.
Primary Skills (AI Native Must Have)
Strong hands on expertise in SAP Build Process Automation (workflows, rules, and automation design).
Solid understanding of business process modeling, orchestration, and exception handling.
Experience integrating automated processes with enterprise systems and APIs.
AI native capability: agentic workflows, retrieval grounded decisions, evaluation loops, and safe automation boundaries.
Secondary / Strongly Beneficial Skills
Business process analysis and optimization experience.
Exposure to low code/no code development paradigms at enterprise scale.
Familiarity with integration platforms and event driven architectures.
Strong documentation and change management practices for automated processes.
What This Role Does Not Center On
Training or fine tuning foundation AI models.
Simple task automation without governance, observability, or intelligence.
Value Delivered
Faster process delivery through reusable, intelligent automation patterns.
Higher efficiency and better outcomes via AI guided decisioning and dynamic workflows.
Scalable, compliant automation foundations that enable the transition from automation to autonomy.
Additional Information
A 15 years full time education is required
职位要求
15 years full time education
