Senior AI Architect

Icreon

Dadri

On-site

INR 6,000,000 - 9,000,000

Full time

14 days+

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Job summary

Icreon is seeking a Senior AI Engineer / AI Solution Architect to own the architecture and evolution of an AI-native Payments Operating System. The role maps end-to-end payment operations, identifies automation opportunities, and defines a pragmatic roadmap for near-term value and long-term modernization.

You will lead architecture reviews and coordinate with risk, compliance, and executives to drive scalable, secure solutions.

Qualifications

  • 10+ years of software engineering, solution architecture, enterprise architecture, or platform engineering experience.
  • At least 3 years designing Generative AI, LLM, machine-learning, or intelligent automation solutions.
  • Experience leading architecture for enterprise-scale transformation programs.
  • Strong Payments or Financial Services experience, ideally involving payment processing, reconciliation, settlement, ledgers, routing, or operational controls.
  • Experience defining target-state architecture, transition architecture, technology roadmaps, and implementation governance.
  • Experience engaging senior business, engineering, risk, compliance, audit, and executive stakeholders.

Responsibilities

  • Assess end-to-end Payments operations, including reconciliation, routing, settlement, reporting, controls, audit, exceptions, and incident management.
  • Identify manual effort, operational bottlenecks, control weaknesses, integration failures, data gaps, and architecture complexity.
  • Define a prioritized Payments AI and automation roadmap based on business value, risk, feasibility, scalability, and ROI.
  • Design the target AI-native Payments Operating System, including agent architecture, orchestration, data pipelines, model access, integration, controls, reporting, and observability.
  • Design an agentic Payments layer that operates alongside the current technology stack and supports gradual migration toward a future-state platform.
  • Define patterns for AI gateways, model selection, prompt and agent registries, RAG/knowledge services, workflow engines, human approval, and auditability.
  • Evaluate and simplify the existing Payments technology landscape, reducing duplication and improving interoperability.
  • Ensure architecture incorporates security, data governance, model risk, explainability, resilience, privacy, and regulatory controls by design.
  • Lead architecture reviews, proof-of-value initiatives, technical standards, reusable frameworks, and platform capability development.
  • Represent Payments within the AI Center of Excellence and align with enterprise AI, data, cloud, security, and governance strategies.
  • Communicate architecture, investment choices, risks, and roadmaps to engineering leaders, business stakeholders, risk, compliance, and executives.
  • Mentor engineers and provide technical leadership from discovery through production optimization.

Skills

AI architecture
Agent orchestration
Enterprise architecture
Payments architecture
Platform architecture
Governance
Roadmapping

Tools

Spring AI
LangGraph
LangChain
MCP
Semantic Kernel
AutoGen

Job description

Position Summary

We are seeking a Senior AI Engineer / AI Solution Architect to own the architecture and evolution of an AI-native Payments Operating System. This role will map end-to-end payment operations, identify automation opportunities and capability gaps, define the target architecture, and establish a pragmatic roadmap that delivers near-term value while enabling long-term platform modernization. The role requires a strong combination of Payments domain knowledge, enterprise architecture, AI platform design, integration strategy, governance, and stakeholder leadership.


Key Responsibilities


  • Assess end-to-end Payments operations, including reconciliation, routing, settlement, reporting, controls, audit, exceptions, and incident management.

  • Identify manual effort, operational bottlenecks, control weaknesses, integration failures, data gaps, and architecture complexity.

  • Define a prioritized Payments AI and automation roadmap based on business value, risk, feasibility, scalability, and ROI.

  • Design the target AI-native Payments Operating System, including agent architecture, orchestration, data pipelines, model access, integration, controls, reporting, and observability.

  • Design an agentic Payments layer that operates alongside the current technology stack and supports gradual migration toward a future-state platform.

  • Define patterns for AI gateways, model selection, prompt and agent registries, RAG/knowledge services, workflow engines, human approval, and auditability.

  • Evaluate and simplify the existing Payments technology landscape, reducing duplication and improving interoperability.

  • Ensure architecture incorporates security, data governance, model risk, explainability, resilience, privacy, and regulatory controls by design.

  • Lead architecture reviews, proof-of-value initiatives, technical standards, reusable frameworks, and platform capability development.

  • Represent Payments within the AI Center of Excellence and align with enterprise AI, data, cloud, security, and governance strategies.

  • Communicate architecture, investment choices, risks, and roadmaps to engineering leaders, business stakeholders, risk, compliance, and executives.

  • Mentor engineers and provide technical leadership from discovery through production optimization.


Required Experience


  • 10+ years of software engineering, solution architecture, enterprise architecture, or platform engineering experience.

  • At least 3 years designing Generative AI, LLM, machine-learning, or intelligent automation solutions.

  • Demonstrated experience leading architecture for enterprise-scale transformation programs.

  • Strong Payments or Financial Services experience, ideally involving payment processing, reconciliation, settlement, ledgers, routing, or operational controls.

  • Experience defining target-state architecture, transition architecture, technology roadmaps, and implementation governance.

  • Experience engaging senior business, engineering, risk, compliance, audit, and executive stakeholders.


Mandatory Technical and Architecture Skills


  • AI architecture: LLM platforms, multi-agent systems, tool calling, RAG, embeddings, vector stores, model gateways, evaluation, and guardrails.

  • Agent orchestration: Spring AI, LangGraph, LangChain, MCP, Semantic Kernel, AutoGen, or comparable frameworks.

  • Enterprise architecture: microservices, event-driven architecture, API strategy, integration platforms, domain-driven design, and distributed systems.

  • Payments architecture: transaction flows, reconciliation, settlement, payment routing, ledger interaction, exception handling, and audit controls.

  • Platform architecture: Kubernetes, cloud platforms, Kafka/event streaming, API gateways, CI/CD, observability, security, IAM, and data pipelines.

  • Governance: risk tiering, data classification, model risk, access control, traceability, explainability, human oversight, and audit logging.

  • Roadmapping: value assessment, architectural trade-offs, dependency management, phased migration, cost modeling, and ROI measurement.


Preferred / Nice-to-Have Skills


  • ISO 20022, SWIFT, ACH, real-time payments, card networks, merchant acquiring, payment gateways, or treasury operations.

  • PCI DSS, SOC 2, model risk management, responsible AI, privacy regulations, and banking control frameworks.

  • TOGAF, cloud architecture, security, or payments-related certifications.

  • Experience establishing AI Centers of Excellence, engineering standards, reference architectures, or reusable platform services.

  • Experience balancing legacy modernization with incremental delivery and measurable business outcomes.

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