Open to research collaboration
GenAI platforms, agentic workflows, research, and open source

Goutam Adwant

Principal Engineer & Independent Researcher

San Francisco Bay Area, CA

Principal Engineer in an S&P 500 enterprise focused on GenAI and agentic solutions using AWS services, Python, LangGraph, MCP, LLMs, and in-house AI infrastructure.

Years building distributed systems
13+
Research papers and datasets
9
Published open-source packages
12
AI-focused papers reviewed
65+
View Profile HighlightsContact Goutam

Profile Highlights

Research, open source, and current engineering leadership

Organized around public work, current production AI platform responsibility, and the systems that connect research with shipping software.

S&P 500 enterprise

Current Principal Engineering Role

Building production GenAI and agentic systems using AWS services, Python, LangGraph, MCP, LLMs, and in-house AI infrastructure, while shaping secure, scalable platform capabilities inside a large public enterprise.

  • Chatbots, agentic workflows, and AI-powered product capabilities
  • AWS services, Python, LangGraph, MCP, LLMs, and in-house AI infrastructure
  • Architecture and infrastructure stacks for production AI platforms

Public manuscripts

Research Papers & Active Work

Research manuscripts and datasets across generative AI policy, RAG evaluation, hybrid cloud-edge intelligence, model editing, and knowledge agents.

  • 9 research works
  • SSRN and TechRxiv preprints
  • Zenodo dataset
  • Direct paper links

Public engineering output

Open Source Systems

Published libraries for MCP security, RAG evaluation, LLM fleet routing, performance linting, tracing, schemas, and prompt contracts.

  • 11 PyPI packages
  • PromptSpec-J on Maven
  • 62 upstream OSS contributions
  • Technical blog

Verified reviewer activity

Peer Review Service

Reviewed 65+ AI-focused manuscripts across IEEE, ACM, and Springer venues, with additional reviews in progress across journals and conferences with selective technical review standards.

  • IEEE Access and IT Professional
  • IEEE TPAMI and Neural Computing and Applications
  • ACM AI and Agentic Systems, ACM TOSEM, IEEE TNSE

Research & Publications

Research papers and active work

Publications and datasets across generative-AI policy, retrieval-augmented generation, hybrid cloud-edge intelligence, model editing, and knowledge-agent architectures.

9

Research works

8

Current preprints

Active journal and conference targets
IEEE SoftwareIEEE Communications LettersACM GoodITSUSTAINIEEE ISAIA

Publication index

Newest first · preprints, manuscripts, and datasets

View ORCID record

  1. Latest · Preprint

    Jul 27, 2026

    EventFlowSentry: Reproducible Fault Injection and Metamorphic Testing for Event-Time Streaming Pipelines

    SSRNPreprintDOI 10.2139/ssrn.7193121

  2. Preprint

    May 5, 2026

    A Cross-Sectional Pilot Audit of Accessible University Generative-AI Policies Using a Policy Clarity and Implementation Index

    PreprintDOI 10.21203/rs.3.rs-8876294/v1

  3. Data Set

    Feb 13, 2026

    Policy Clarity and Implementation Index (PCII) Dataset: Cross-Sectional Crawl of University Generative-AI Policies (Feb 2026)

    PublishedDOI 10.5281/ZENODO.18627149

  4. Preprint

    Jan 13, 2026

    Amorphous Intelligence in Hybrid Cloud-Edge Systems: Distributed AI Cognition Without Epistemic Authority

    PreprintDOI 10.36227/techrxiv.176834666.66906312/v1

  5. Preprint

    Jan 13, 2026

    LLM-Powered Contextual Diagnosis Support for Rare Diseases Using Electronic Health Records

    PreprintDOI 10.36227/techrxiv.176834437.73411532/v1

  6. Preprint

    Jan 13, 2026

    Subspace Collisions in Knowledge Editing: Orthogonal Low-Rank Updates for Scalable, Stable Model Edits

    PreprintDOI 10.36227/techrxiv.176834437.78088768/v1

  7. Preprint

    Jan 10, 2026

    From Chatbots to Knowledge Agents: Evidence-Aware Architectures for Long-Horizon Generative AI Systems

    PreprintDOI 10.36227/techrxiv.176800991.12749719/v1

  8. Preprint

    Jan 8, 2026

    Evidence Coverage Evaluator: A Comprehensive Framework for Assessing Grounding Quality in Retrieval-Augmented Generation Systems

    PreprintDOI 10.36227/techrxiv.176784505.56675782/v1

  9. Preprint

    Jan 8, 2026

    RAG as a Scientific Instrument: Measuring Evidence Completeness, Uncertainty, and Knowledge Gaps in Generative AI Systems

    PreprintDOI 10.36227/techrxiv.176784506.69820111/v1

Academic Service & Peer Review

Invited reviewer across premier AI venues

Serving as an invited reviewer for top-tier IEEE, ACM, and Springer journals and conferences, with 65+ AI-focused manuscript reviews completed and additional reviews in progress.

65+

AI-focused reviews

9

Venues served

3

Publishers

Professional Memberships
IEEE · Senior MemberIET · Member
IEEE

IEEE Access

Invited Reviewer

IEEE

IEEE Transactions on Pattern Analysis and Machine Intelligence

Invited Reviewer

ACM

ACM Conference on AI and Agentic Systems

Invited Reviewer

IEEE

IEEE Transactions on Mobile Computing

Invited Reviewer

ACM

ACM Transactions on Software Engineering and Methodology

Invited Reviewer

Springer

Neural Computing and Applications

Invited Reviewer

IEEE

IEEE Open Journal of the Computer Society

Invited Reviewer

IEEE

IEEE Transactions on Network Science and Engineering

Invited Reviewer

IEEE

IT Professional

Invited Reviewer

Reviewer Certifications

Introduction to Peer Review

Web of Science Academy

View credential

Certified Peer Reviewer

Elsevier BV (Netherlands)

View credential

ACM Certified Peer Reviewer

Association for Computing Machinery

View credential

Serving as invited reviewer across IEEE, ACM, Springer

Engineering Open Source

Published libraries and developer tools

12 published packages
PyPIGitHub

bigocheck

bigocheck

Zero-dependency, AI-assisted Big-O complexity checker. Static analysis + empirical benchmarking for Python.

PythonPyPIcomplexitybig-o
PyPIGitHub

kvfleet

kvfleet

Production-grade, KV-cache-aware intelligent routing for self-hosted and hybrid LLM fleets.

PythonPyPIgpu-routinginference-routing
PyPIGitHub

mcp-egress-guard

mcp-egress-guard

Local-first MCP reverse proxy that blocks sensitive, destructive, or policy-violating tool calls before execution using deterministic rules, DLP matchers, and AST-based intent analysis.

PythonPyPIagent firewalldata loss prevention
PyPIGitHub

mcp-pool

mcp-pool

Async connection pool for Model Context Protocol (MCP) client sessions — keep sessions warm, reuse across requests, auto-reconnect on failure.

PythonPyPIagentasync
PyPIGitHub

mcp-shield-pii

mcp-shield-pii

Intercepting gateway proxy for MCP clients/servers — real-time PII redaction with regex, NLP, and optional subinterpreter concurrency

PythonPyPIgdprhipaa
PyPIGitHub

pdperf

pdperf

A static performance linter that detects slow Pandas anti-patterns before they reach production.

PythonPyPIpandasperformance
PyPIGitHub

pydanticforge

pydanticforge

Infer robust Pydantic v2 models from messy, evolving JSON streams

PythonPyPIclicode-generation
PyPIGitHub

schemaglow

schemaglow

Human-friendly schema diff and contract drift detection for CSV, JSON, JSONL, Parquet, OpenAPI, Avro, and protobuf.

PythonPyPIavrocli
PyPIGitHub

toolcallcheck

toolcallcheck

Deterministic Python testing for tool-using agents. Mock MCP tools, assert exact tool calls and trajectories, verify headers, and run offline in CI.

PythonPyPIagent-testingai-agents
PyPIGitHub

tracemap

tracemap

Modern traceroute visualizer for the terminal with TUI, interactive HTML maps, and ASN/GeoIP lookups.

PythonPyPIasciidebugging
PyPIGitHub

vectormigrate

vectormigrate

Python-first tooling for safe embedding-model migration across vector retrieval systems.

PythonPyPIai-infrastructureembeddings
MavenGitHub

promptspecj

PromptSpec-J

A suite of Java libraries for LLM prompt specifications. Includes sub-modules: promptspec-model, promptspec-parser, promptspec-validator, promptspec-runtime, promptspec-codegen-java, promptspec-spring-ai-adapter, promptspec-junit5, and promptspec-maven-plugin.

JavaMavenPrompt Engineering

Open-source contributions

Contributions across the open-source ecosystem

62 documented contributions

62 shown

openclaw/openclaw · #119520 · Merged Aug 9, 2026

Remove deleted cron job sessions

Fixed OpenClaw cron removal so deleted isolated cron jobs also clean up their reusable base sessions and no longer appear as ghost entries in session-management surfaces.

Merged upstream7 files+603 / -11cron sessions
Issue

Deleting a cron job removed its cron definition but left the agent:<agent>:cron:<jobId> session record behind. Operators could still see deleted jobs in the Control UI session dropdown even though the job itself was gone.

Fix

Ran session cleanup after durable cron-definition removal through the canonical session lifecycle mutation, added guarded cleanup for exact active-run markers, and fenced same-ID replacement across sibling CronService instances sharing the same cron store.

Technical value
  • Removes ghost cron sessions from the session store and Control UI after isolated/current jobs are deleted.
  • Preserves active runs, shared main sessions, unrelated jobs, and per-run history governed by cron retention.
  • Prevents same-ID recreation races by making replacement wait for the previous job's asynchronous session cleanup to finish.
Validation
  • Added a dedicated remove-session-cleanup suite covering isolated sessions, active markers, replacement fencing, sibling services, and session reaper behavior.
  • Documented real CLI/gateway proof against isolated SQLite state showing the cron job and base session were both gone after removal.
  • Merged with 7 focused cron/session test files and 138 passing tests documented on the PR.
cron removal lifecyclesession cleanup mutationactive job markerscron service lock fencingsession reaper behavior
TypeScriptOpenClawCronServiceSession state
Open pull requestOpen GH-46369Open merged commit

Experience Timeline

Leadership arc across systems engineering and AI research

A concise progression through graduate systems work, platform engineering, principal engineering responsibility, and independent research output.

  1. 2014 - 2016

    M.S. in Software Engineering

    San Jose State University

    Graduate foundation in software architecture, scalable systems, and disciplined engineering delivery.

    Software architectureDistributed systemsResearch

  2. 2015 - 2017

    Big Data and Platform Engineering

    Hewlett Packard Enterprise

    Built data-intensive platform capabilities and production pipelines across enterprise engineering environments.

    JavaPythonData pipelinesPlatform

  3. 2017 - Present

    Principal Engineer

    S&P 500 enterprise

    Builds GenAI and agentic solutions using AWS services, Python, LangGraph, MCP, LLMs, and in-house AI infrastructure. Designs scalable, secure infrastructure stacks for production AI platforms.

    AWS servicesLangGraphMCPPython

  4. Current

    Independent Researcher

    Applied AI and open-source systems

    Bridges production AI architecture with LLM evaluation, RAG reliability, cloud-edge AI behavior, and public developer tooling.

    LLMsRAGAWSOpen source

Technical Depth

Engineering stack and platform depth

Hands-on architecture depth across Java, Python, Spring Boot, Docker, Terraform, CI/CD, applied AI infrastructure, and data-intensive microservices.

Cloud Architecture

AWS-first distributed systems with pragmatic reliability boundaries.

AWSTerraformDockerCI/CDObservability

Backend Systems

Data-intensive services built for maintainability and operational clarity.

JavaPythonSpring BootMicroservicesREST

Applied AI

Production-ready GenAI, agentic workflow, RAG, and evaluation pipelines with clear measurement and traceability.

LLMsRAGLangGraphMCPAgentic workflows

Developer Platforms

Tooling that moves quality gates earlier into local development and CI.

ASTMCPPyPIMavenAutomation

From the Blog

Technical notes from the build path

Long-form writing on AI infrastructure, distributed systems, and the engineering trade-offs behind public libraries.

View all posts

1 technical posts

Open Source Systems

kvfleet routing internals

kvfleet Internals: Building a KV-Cache-Aware Routing Control Plane for LLM Fleets

A deep technical walkthrough of kvfleet's routing engine, from prompt fingerprinting and KV-cache affinity to policy-aware model selection, fallback chains, and OpenAI-compatible gateway mode.

kvfleetllm-routingkv-cachepython

Contact

Let's build something meaningful

Whether it's a research collaboration, open source contribution, or technical advisory — I'm always open to conversations that push the boundaries of AI and distributed systems.

Based in San Francisco Bay Area, CA.

Pacific Time (PT) · Usually within 24 hours

workwithgoutam@gmail.com
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