Job Description
Solution Architect — Agentic Finance Solution Job Title: Solution Architect — Agentic Platform

Location:
Noida, Gurgaon, Bangalore, Pune

Experience:
12+ Years Tech Stack: LLMs
· Multi-Agent Frameworks
· Azure
· Python
· Enterprise Integration Job Summary We are looking for a Agentic Solution Architect to lead the end-to-end architectural design of a next-generation agentic platform for Finance and Accounting operations. This is a foundational role — you will define how AI agents are designed, orchestrated, and governed across Purchase-to-Pay, Order-to-Cash, and Record-to-Report workflows, and you will own the architectural decisions that determine whether this platform can scale across dozens of client implementations without custom engineering work for each. This role demands a rare combination: deep hands-on experience with LLMs and multi-agent systems, strong enterprise software architecture credentials, and enough Finance and Accounting domain literacy to make architectural trade-offs that are grounded in how finance operations actually work. You will collaborate with a cross-functional engineering team, work directly with client stakeholders and delivery leadership, and set the technical direction that AI engineers, backend engineers, integration specialists, and frontend engineers all build toward. You will not just design on whiteboards — you are expected to be hands-on enough to validate architectural decisions through prototypes, review critical implementation choices, and course-correct when the team's execution drifts from the intended design.

Key Responsibilities
• Own the end-to-end technical architecture of the agentic platform — including agent orchestration framework, HITL engine, exception routing, integration layer, intelligence services, canonical data model, and workflow state store — ensuring all components are cohesive and scalable by design.
• Define the multi-agent design patterns used across the platform — agent boundaries, tool use contracts, inter-agent communication protocols, confidence thresholds, fallback routing, and human handoff triggers — and govern their consistent application across all workflow implementations.
• Lead the design of the workflow state management architecture — covering execution context persistence, checkpointing, idempotent retries, long-running process patterns,



and safe resume — ensuring finance workflows that span days or weeks behave correctly under failure conditions.
• Establish the observability and governance architecture — structured logging, distributed tracing, model performance monitoring, SLA tracking, audit trail design, and compliance logging — ensuring the platform meets the control requirements of regulated finance environments.
• Evaluate and select foundational technologies — LLM providers, agentic frameworks (LangGraph or AutoGen or CrewAI), orchestration engines (Azure Durable Functions or Temporal), vector databases, and messaging infrastructure — with clear justification for each choice.
• Lead technical design reviews and architecture governance — reviewing critical implementation decisions made by AI engineers, backend engineers, and integration engineers, and ensuring they align with the platform's intended design.
• Work directly with client technical stakeholders during pre-sales, solutioning, and delivery — explaining architectural decisions, assessing client infrastructure constraints, and adapting the platform design to client-specific requirements without compromising reusability.
• Define and enforce non-functional requirements across the platform — latency SLAs, throughput targets, availability requirements, disaster recovery posture, and security controls — and validate that the implementation meets them.
• Build and maintain the technical roadmap for the platform — sequencing capability development, managing architectural debt, and ensuring the platform evolves coherently as new workflows and client requirements are added.
• Mentor and technically grow the engineering team — establishing architecture decision record (ADR) practices, conducting design reviews, and developing engineering standards that the team follows consistently. Required Skills
• 12+ years of software architecture and engineering experience, with at least 3 years focused on AI/ML systems and at least 2 years hands-on with LLM-based or agentic applications in production.




• Deep expertise in multi-agent system design — agent orchestration, tool use, inter-agent communication, stateful agent patterns, and human-in-the-loop architecture using frameworks such as LangGraph, AutoGen, CrewAI, or equivalent.
• Proven experience architecting event-driven, distributed systems on Azure at scale — Azure Durable Functions, Azure Service Bus, Azure Event Grid, Azure Functions, Azure Container Apps (AKS), Azure API Management, Azure Database for PostgreSQL, and related services.
• Solid Python skills— sufficient to prototype architectural patterns, review implementation code critically, and validate that the team's code matches the intended design.
• Experience with MLOps and AI governance — model versioning, drift detection, evaluation pipelines, prompt management, and production monitoring for LLM-based services.
• Strong communication skills — able to explain complex architectural decisions to both engineering teams and non-technical client stakeholders, and to produce clear, concise architecture documentation.
• Demonstrated ability to make and defend technology selection decisions with clear trade-off analysis — including build vs. buy, framework selection, and infrastructure design choices.
• Hands-on experience delivering agentic or LLM-based systems in a finance, BPO, or shared services context — not just proof-of-concept projects but production deployments with real operational volume and compliance requirements. Preferred Qualifications
• Deep familiarity with Finance and Accounting operations — P2P, O2C, and R2R processes, exception patterns, compliance controls, and the operational metrics (STP rate, first-pass match rate, exception aging) that define platform success.
• Experience architecting RAG pipelines, vector search infrastructure, and document intelligence services for structured extraction from financial documents at scale.
• Experience with architecture governance frameworks — Architecture Decision Records (ADRs), architecture review boards, and technical standards documentation.
• Prior experience in a shared services, or F&A; technology consulting context — understanding how finance operations teams work and what makes a platform adoptable by non-technical operations staff.
• Contributions to open-source AI/agentic projects or published technical writing on multi-agent system design.

📌 Solution Architect — Agentic Finance Solution (Noida)
🏢 EXL
📍 Noida