Raghunath Manyam

22 years architecting AI-augmented cloud-native systems for regulated-industry workloads — finance, insurance, mainframe modernization. Currently leading an 18-engineer reinsurance modernization at a Tier-1 carrier and sole architect of a Claude-based agentic COBOL→TypeScript factory in internal production use; previously owned ITIL operations across 150 applications with 14 direct and ~50 indirect reports.

Signature work

• Modernization Factory — Agentic COBOL→AWS Pipeline
  2025 – Present · Cognizant — Financial Services Client

  8-stage Claude pipeline: JCL + COBOL → Lambda + Step Functions + Aurora DDL + parity tests

• Enterprise Reinsurance — Data Migration and Reporting
  2020 – 2024 · Cognizant — Financial Services Client

  Metadata-driven cloud ETL + event-driven reporting platform

• Enterprise Reinsurance — Cash Clearance
  2020 – 2024 · Cognizant — Financial Services Client

  Full-stack serverless app for high-volume transaction clearance

Career

• Lead Engineer
  Cognizant — Financial Services Client · Sep 2020 – Present

  Enterprise Reinsurance modernization at a Tier-1 carrier — a 25+ year-old PL/I + DB2-LUW system carrying $billions in active treaty exposure, with ~50 daily actuarial and finance consumers and no write-freeze tolerance. Own technical direction for 18 engineers across data, application, and reporting tracks. Designed the metadata-driven migration pattern that collapsed the 23-table mainframe → Aurora migration into 3 Glue jobs (vs. ~69 the obvious design called for); architected the Cash Clearance latency win with DynamoDB caching over partitioned Aurora reads. Cut Cash Clearance search latency from 3–5 minutes to <5 seconds on 100K+ row queries; shipped the event-driven reporting layer feeding ~50 treaty and finance consumers. Also sole architect and builder of the Modernization Factory — an agentic pipeline (built as an MCP server) that turns JCL + COBOL into AWS Lambda, Step Functions, and Aurora DDL with a parity test suite. Its 8 stages route per-stage across Claude tiers — Haiku for the triage gate, Sonnet for structured extraction and codegen, Opus with extended thinking for the one architectural-routing decision and the parity-test design — roughly 70–80% cheaper than running Opus throughout. Human-in-the-loop by default: the pipeline pauses for schema review before it writes any code. In internal production use, output shipping after minor human review.

• Project Manager — Operations
  Cognizant — Financial Services Client · May 2017 – Dec 2019

  L1–L3 application operations across a 150-system production portfolio under ITIL delivery — every reactive ticket triage came out of the same team's hours. Owned operational outcomes for 14 direct and ~50 indirect reports. Stood up the team's first proactive monitoring + alerting layer so every shift ran off shared dashboards; drove the focus from triage volume to root-cause elimination — identifying repeat incidents and shipping permanent fixes rather than re-running the same ticket loop. Improved portfolio stability by 60% over three years.

• Sr Software Engineer
  Cognizant — Financial Services Client · Jun 2007 – Apr 2017

  Major rating-engine re-platform at a US personal-lines carrier — the actuarial business owned the rules but couldn't change them without an engineering round-trip, because they lived as 100+ hardcoded PL/I procedures over IMS-DB lookups. Owned the business-logic analysis track. Translated 100+ rating algorithms into Ratabase semantics — each validated against an actuarial SME; ran re-rate cycles across full state policy books when rating errors surfaced; pair-designed the Informatica + PowerExchange data pipelines with the Principal architect. Individual re-rate cycles returned several-hundred-thousand-dollar customer refunds; the pipeline became the data backbone for actuarial pricing and underwriting decisioning.

• Software Engineer
  Cognizant — Financial Services Client · Apr 2004 – May 2007

  Entry into regulated-industry tech — production support and feature work on P&C insurance applications. Owned DB2 SQL performance tuning on claims workloads, requirements analysis with business analysts, and quality audits across the application portfolio. Built the mainframe-adjacent data, release-discipline, and customer-money instincts every later role compounded on.