Ayush Ranjan Roy
AI Engineer at Accenture. Multi-agent systems, MCP, and human-in-the-loop workflows.
I build multi-agent systems for enterprise finance workflows (Order-to-Cash / Dispute & Deduction) with LangGraph, MCP tool access, and human review. Previously platform engineering on Accenture’s MxDR / Adaptive MxDR product on AWS — including OpenTelemetry, Datadog, and SIEM telemetry.
Claude Certified Architect — Foundations · Anthropic, May 2026
Experience
Aug 2025 — Present
AI Engineer · Accenture
GenAI & Data
- Multi-agent systems for enterprise Order-to-Cash / Dispute & Deduction using LangGraph, FastAPI, and PostgreSQL — durable state so long-running workflows resume reliably.
- MCP tool access so agents call production tools under policy instead of unconstrained side effects.
- Human-in-the-loop gates so uncertain or high-impact steps pause for analyst approval before the run continues.
- Multi-model inference (Claude, GPT, Azure) with async execution, routing, retries, and latency / token / cost metrics for evaluation.
LangGraphMCPHITLClaudeGPTAzure AIFastAPIPostgreSQLAug 2023 — Aug 2025
Platform Engineer · Accenture
Security · MxDR / Adaptive MxDR
- AWS platform for MxDR → Adaptive MxDR: Terraform, CI/CD, and production support across shared services and multi-account environments.
- Redis-backed shared metadata services; Lambda upgrades (Python 3.8 → 3.12); multi-environment operations.
- Secrets Manager and IAM automation; service hardening; restricted-egress proxy automation.
- Observability on the security platform: OpenTelemetry health paths, Datadog monitoring, mTLS telemetry into enterprise SIEMs; blue-green deploys on live upgrades.
AWSTerraformRedisOpenTelemetryDatadogSecrets ManagerIAMCI/CD
Selected work
Multi-agent finance workflows
Enterprise · GenAILangGraph multi-agent systems for Order-to-Cash / Dispute & Deduction — MCP tools, human review gates, FastAPI, PostgreSQL. Contributor on a multi-engineer team.
LangGraphMCPHITLFastAPIPostgreSQLMCP + human-in-the-loop
Enterprise · GenAIMCP servers and tool bindings for governed agent tool use, with human approval before high-impact actions.
MCPHITLLangGraphMulti-model inference
Enterprise · GenAIAsync inference across Claude, GPT, and Azure with concurrency control, retries, routing, and latency / token / cost metrics.
ClaudeGPTAzure AIAsync PythonMxDR → Adaptive MxDR on AWS
Enterprise · PlatformPlatform modernization: Terraform, shared services, CI/CD, secrets, plus OpenTelemetry, Datadog, and SIEM health telemetry.
AWSTerraformOpenTelemetryDatadogRedisHelixOps
Open sourceIncident IDE: multi-agent RCA over runbooks, then human-approved fixes. Mock-safe by default.
LangGraphRAGFastAPIHITL
About
AI engineer at Accenture (GenAI & Data). I build multi-agent systems with LangGraph, MCP for governed tool calls, human-in-the-loop review, FastAPI, and PostgreSQL — on multi-engineer teams shipping enterprise finance workflows.
I also build multi-model inference (Claude, GPT, Azure): async execution, routing, retries, and latency / token / cost metrics.
2023–2025: platform engineer on Accenture Security’s MxDR → Adaptive MxDR product — Terraform, shared services, CI/CD, secrets, and production observability (OpenTelemetry, Datadog, SIEM) on AWS.
Open source: HelixOps, RAGGym. Gurugram. Open to senior AI roles.
Education
B.Tech, Electronics and Communication Engineering · VIT Chennai, 2019–2023
