Arjol Pengu

Experience

• 2026 - Present

  GenAI Manager @ PwC

  New York - Remote

  AI-Powered Pharmaceutical Sales Platform (Fortune 50 Client)

  Led architecture, product strategy, and engineering delivery of a production AI sales platform for a Fortune 50 pharmaceutical client. Owned the full lifecycle from system design through deployment across two cloud environments, managing a cross-functional team of engineers, data scientists, and QA.

  Responsibilities:

  • Architected a 24-node LangGraph agentic pipeline processing real-time healthcare conversations with deterministic compliance enforcement, deployed to the client's production Kubernetes cluster.
  • Designed and shipped a hybrid RAG retrieval system (pgvector + sparse search + quality gating) that improved response accuracy from 36% to 88% while maintaining 100% regulatory safety across 30 compliance probes.
  • Led a cross-functional engineering team across 3 parallel workstreams (guardrails, content, evaluation), creating sprint plans with day-level task assignments and dependency tracking.
  • Built a multi-suite AI evaluation framework covering 214 functional test cases, a 760-probe adversarial red team corpus, and behavioral tone scoring, integrated with Langfuse for observability and trend reporting.
  • Designed 14 AI safety guardrails (PHI detection, adverse event screening, off-label blocking, prompt injection defense) using a layered architecture: deterministic rules as the fast path, LLM-based classification for the long tail.
  • Delivered a 2-week remediation sprint closing 10 legal review findings (3 critical) from an external law firm assessment, coordinating 3 parallel workstreams with day-by-day engineering assignments.
  • Owned the platform migration from AWS ECS to the client's Kubernetes environment, creating Helm charts, CI/CD pipelines, and ensuring data parity across both production environments.
  • Ran 10+ live client demos and authored scenario-based talk tracks, translating technical architecture decisions into product feedback sessions with the client's product and medical-legal teams.
  • Authored a scalability analysis identifying 7 bottlenecks blocking 1,000+ concurrent users, modeling token throughput requirements from production traces and delivering infrastructure sizing recommendations.
  • Defined the product evaluation framework adopted by the client's product, engineering, and regulatory teams to measure AI quality across safety, accuracy, fidelity, and conversational tone.

  Achievements:

  • Shipped a production agentic AI platform: LangGraph pipeline, hybrid RAG retrieval, semantic caching, 33 configurable skills, and 14 compliance guardrails, serving real users in a regulated pharmaceutical environment.
  • Improved response quality from 36% to 88% on the functional evaluation suite while holding regulatory safety at 100% across all iterations.
  • Built and deployed a RAG ingestion pipeline processing 7 source documents into 288 provenance-tracked chunks with automated extraction, metadata tagging, and content verification.
  • Led a cross-functional remediation sprint that closed 3 critical regulatory findings within 2 weeks, preventing production-blocking issues before the client's launch timeline.
  • Authored 37 wiki pages and 64+ architecture documents, establishing the engineering team's canonical reference for system design, onboarding, and client-facing technical presentations.

  • Python
  • LangGraph
  • FastAPI
  • pgvector
  • React
  • TypeScript
  • AWS
  • Kubernetes
  • Terraform
  • PostgreSQL
• 2024 - 2026

  Senior Software Engineer @ EY

  Troy, New York - Remote

  AI-Powered Financial Platform

  Led greenfield AI-powered financial platform and scaled high-volume Python microservices on Azure.

  Responsibilities:

  • Defined and implemented financial models using S&P500 data for AI-driven financial insights.
  • Led development of AI-powered solution leveraging agent-to-agent communication, prompt engineering, and response validation.
  • Collaborated with cross-functional and AI teams to enhance existing AI capabilities (RAG, Direct Query).
  • Managed engineer workloads to ensure timely stakeholder delivery.
  • Developed and scaled distributed Python microservices using FastApi and Microsoft Azure.
  • Architected and operated integration services with third-party applications.

  Achievements:

  • Architected greenfield AI financial platform improving stakeholder financial insights through advanced AI modeling.
  • Implemented robust prompt engineering and validation ensuring appropriate AI-generated responses.
  • Designed and deployed scalable microservice architecture, improving system reliability.

  • Python
  • FastAPI
  • AI/ML
  • Prompt Engineering
  • RAG
  • Agent-Based Systems
  • Azure
  • Microservices

  Management System for Protecting Workers Rights (MPWR)

  Developed and scaled high-volume Java microservices on GCP, integrating third-party services, leading API architecture, collaborating with cross-functional teams, and optimizing platform performance.

  Responsibilities:

  • Developed and scaled distributed, high-volume Java microservices using Spring Boot and Google Cloud Platform to support client needs.
  • Architected and operated integration services with third-party applications like Microsoft Dynamics, leveraging RESTful APIs and OData.
  • Collaborated with cross-functional teams and stakeholders to design, develop, and optimize APIs for service-to-service integrations.
  • Led deployment and maintenance of production microservices, ensuring scalability and reliability for user identity management and platform auditing.
  • Designed and developed a critical integration microservice, managing communication and data flow between third-party services using modern Java technologies.

  Achievements:

  • Secured multiple DOL contracts through consistent results, totalling over 70M in revenue in the span of 3 years.
  • Designed and deployed a scalable microservice architecture, improving system reliability and reducing downtime.
  • Developed reusable API solutions and enhanced security, increasing development efficiency and compliance.

  • Postgres
  • Java
  • GitHub
  • GCP
  • Angular
  • Springboot
  • Docker
  • Kubernetes
• 2021 - 2024

  Software Engineer II @ Nuvalence (acquired by EY)

  Troy, New York - Remote

  Summary:

  • Designed scalable microservices, led auditing architecture, developed APIs, optimized workflows, and enhanced system performance using Java Spring, Camunda, and cloud technologies.

  Responsibilities:

  • Designed and led the development of a scalable distributed microservice platform for regulatory paperwork automation, leveraging Java Spring Boot, PostgreSQL, and Camunda.
  • Architected and implemented a comprehensive auditing system, enhancing compliance tracking and user confidence.
  • Developed and orchestrated license life cycle workflows using Camunda and OpenAPI, ensuring seamless automation.
  • Integrated Google Identity and Firebase for user management and leveraged LibreOffice for automated document generation
  • Led infrastructure architecture and DevOps efforts, managing full software lifecycle with Jenkins and Terraform.

  Achievements:

  • Led the development of a scalable microservice platform that streamlined regulatory paperwork processing, significantly improving efficiency and reducing manual effort.
  • Architected a high-performance pricing engine leveraging AWS services, enhancing accuracy and efficiency for client-specific pricing models.
  • Developed an automated license lifecycle workflow using Camunda, reducing processing time and ensuring seamless regulatory compliance.
• 2019 - 2021

  Software Engineer @ 3M

  Albany, New York - In Office

  Summary:

  • Developed and optimized a health data platform using AWS, Python, Apache Spark, and CI/CD technologies.

  Responsibilities:

  • Led development of a centralized health data platform on AWS, leveraging Python and microservices for Big Data processing.
  • Utilized distributed technologies like Apache Spark, Hive, Pandas, and AWS Glue to transform large datasets for customer value.
  • Designed and implemented RESTful APIs with API Gateway for seamless integration and user-friendly interfaces for customers and engineers.
  • Evaluated emerging technologies to enhance platform scalability and meet complex business requirements.
  • Collaborated with cross-functional teams to architect infrastructure and manage the full software lifecycle using AWS CI/CD tools.
  • Worked closely with stakeholders to understand and implement technical solutions for their business needs.

  Achievements:

  • Successfully developed and scaled a health data platform capable of handling high-volume Big Data, enhancing both customer and business user experiences.
  • Streamlined data processing workflows by integrating Apache Spark, AWS Glue, and other technologies, significantly improving operational efficiency and data accuracy.