- Location
- NOIDA
- Type
- Full-time
- Department
- Engineering
- Experience
- 2+ years
- Closing date
- Today
- Source
- ApplyToJob
Description
Position Summary
We are seeking an AI Automation Engineer to design, build, integrate, and deploy production-grade AI workflows that automate complex Payments operations. The role will develop agentic solutions for reconciliation, audit preparation, reporting, financial analytics, incident handling, and operational exception management.
The successful candidate will combine strong software engineering with LLM orchestration, workflow automation, enterprise integration, and human approval controls.
Key Responsibilities
Design and build AI agents and workflows for reconciliation, audit preparation, reporting, analytics, exception handling, and incident automation.
Use Java/Spring AI or Python-based orchestration to implement robust agentic workflows.
Integrate Claude/Anthropic, OpenAI, Gemini, or equivalent model APIs using secure enterprise patterns.
Build workflow orchestration using n8n, Temporal, Camunda, Airflow, LangGraph, or equivalent platforms.
Integrate payment, finance, reporting, case-management, and data platforms through APIs, events, queues, and data pipelines.
Implement tool calling, structured outputs, validation rules, deterministic checks, and business-rule guardrails.
Embed human-in-the-loop review, approval, escalation, override, and exception-resolution steps.
Ensure workflows are deployable, observable, versioned, auditable, secure, and compliant.
Identify high-value automation opportunities and quantify effort reduction, cycle-time improvement, and control benefits.
Create reusable connectors, workflow templates, agent patterns, prompts, test harnesses, and engineering standards.
Collaborate with Payments operations, backend engineering, architecture, platform, compliance, risk, and audit teams.
Required Experience
5-8 years of software engineering, backend development( Java), integration engineering, or automation experience.
At least 2 years building LLM, Generative AI, machine-learning, or agentic applications.
Experience taking AI solutions beyond proof-of-concept into controlled production environments.
Experience integrating multiple enterprise systems through APIs, events, messaging, or workflow engines.
Experience designing exception handling, approval workflows, and operational controls.
Mandatory Technical Skills
Programming: Java with Spring Boot/Spring AI and/or Python with FastAPI or equivalent frameworks.
Generative AI: Claude/Anthropic APIs, OpenAI APIs, or equivalent; prompt design; tool/function calling; structured outputs.
Agentic frameworks: LangGraph, LangChain, Spring AI, MCP, Semantic Kernel, AutoGen, or equivalent.
Workflow automation: n8n, Temporal, Camunda, Airflow, or comparable orchestration technology.
Integration: REST APIs, event-driven integration, Kafka or RabbitMQ, API gateways, SQL, and data pipelines.
Engineering: Docker, Kubernetes, Git, automated testing, CI/CD, logging, monitoring, and secure configuration management.
Quality and control: unit/integration testing, LLM evaluation, prompt/version management, validation, fallback, retry, and audit logging.
Preferred / Nice-to-Have Skills
Payments or banking operations, including reconciliation, settlement, disputes, routing, reporting, or audit.
ISO 20022, SWIFT, card processing, ACH, real-time payments, payment gateways, or ledger systems.
RAG architectures, embeddings, vector databases, document intelligence, and enterprise knowledge systems.
Cloud-native application development on AWS, Azure, or GCP.
Experience with regulated workflows, data privacy, PCI DSS, or financial controls.
We are seeking an AI Automation Engineer to design, build, integrate, and deploy production-grade AI workflows that automate complex Payments operations. The role will develop agentic solutions for reconciliation, audit preparation, reporting, financial analytics, incident handling, and operational exception management.
The successful candidate will combine strong software engineering with LLM orchestration, workflow automation, enterprise integration, and human approval controls.
Key Responsibilities
Design and build AI agents and workflows for reconciliation, audit preparation, reporting, analytics, exception handling, and incident automation.
Use Java/Spring AI or Python-based orchestration to implement robust agentic workflows.
Integrate Claude/Anthropic, OpenAI, Gemini, or equivalent model APIs using secure enterprise patterns.
Build workflow orchestration using n8n, Temporal, Camunda, Airflow, LangGraph, or equivalent platforms.
Integrate payment, finance, reporting, case-management, and data platforms through APIs, events, queues, and data pipelines.
Implement tool calling, structured outputs, validation rules, deterministic checks, and business-rule guardrails.
Embed human-in-the-loop review, approval, escalation, override, and exception-resolution steps.
Ensure workflows are deployable, observable, versioned, auditable, secure, and compliant.
Identify high-value automation opportunities and quantify effort reduction, cycle-time improvement, and control benefits.
Create reusable connectors, workflow templates, agent patterns, prompts, test harnesses, and engineering standards.
Collaborate with Payments operations, backend engineering, architecture, platform, compliance, risk, and audit teams.
Required Experience
5-8 years of software engineering, backend development( Java), integration engineering, or automation experience.
At least 2 years building LLM, Generative AI, machine-learning, or agentic applications.
Experience taking AI solutions beyond proof-of-concept into controlled production environments.
Experience integrating multiple enterprise systems through APIs, events, messaging, or workflow engines.
Experience designing exception handling, approval workflows, and operational controls.
Mandatory Technical Skills
Programming: Java with Spring Boot/Spring AI and/or Python with FastAPI or equivalent frameworks.
Generative AI: Claude/Anthropic APIs, OpenAI APIs, or equivalent; prompt design; tool/function calling; structured outputs.
Agentic frameworks: LangGraph, LangChain, Spring AI, MCP, Semantic Kernel, AutoGen, or equivalent.
Workflow automation: n8n, Temporal, Camunda, Airflow, or comparable orchestration technology.
Integration: REST APIs, event-driven integration, Kafka or RabbitMQ, API gateways, SQL, and data pipelines.
Engineering: Docker, Kubernetes, Git, automated testing, CI/CD, logging, monitoring, and secure configuration management.
Quality and control: unit/integration testing, LLM evaluation, prompt/version management, validation, fallback, retry, and audit logging.
Preferred / Nice-to-Have Skills
Payments or banking operations, including reconciliation, settlement, disputes, routing, reporting, or audit.
ISO 20022, SWIFT, card processing, ACH, real-time payments, payment gateways, or ledger systems.
RAG architectures, embeddings, vector databases, document intelligence, and enterprise knowledge systems.
Cloud-native application development on AWS, Azure, or GCP.
Experience with regulated workflows, data privacy, PCI DSS, or financial controls.
Skills
PythonJavaFastAPISpring BootAWSAzureGCPDockerKubernetesCI/CDSQLAirflowGitRESTCompliance
