{
  "schemaVersion": "1.0",
  "lastUpdated": "2026-09-18",
  "canonicalUrl": "https://rxbru.vercel.app",
  "identity": {
    "name": "Amar Mahato",
    "handle": "rxbru",
    "location": "India",
    "headline": "Software Engineer",
    "specialization": "Backend Systems + Applied AI",
    "summary": "Software engineer building backend systems and applied-AI products across APIs, realtime systems, databases, retrieval, reliability, internal tools, and agent workflows.",
    "primaryLanguages": [
      "Python",
      "TypeScript"
    ]
  },
  "positioning": {
    "focus": [
      "backend systems",
      "APIs and realtime delivery",
      "databases and durable state",
      "reliability and production debugging",
      "retrieval and agent workflows",
      "cloud and internal tooling",
      "model evaluation and applied AI"
    ],
    "preferredDescription": "Software Engineer focused on backend systems with applied-AI depth",
    "contactStatement": "Backend systems with applied AI.",
    "workingStyle": "I am most useful where software has to hold up: APIs, databases, reliability work, evals, product experiments, internal tools, and applied-AI systems with clear boundaries."
  },
  "education": {
    "credential": "B.Tech in Computer Science and Engineering",
    "institution": "Dr. B.C. Roy Engineering College",
    "location": "Durgapur, West Bengal, India",
    "expectedGraduation": "2027"
  },
  "work": {
    "organization": "IntelGrader",
    "role": "AI Engineer Intern",
    "dates": "May 2026 - Present",
    "location": "Remote",
    "overview": "AI Engineer Intern working across product software, backend reliability, cloud tooling, model evaluation, and coding-agent systems.",
    "workstreams": [
      {
        "name": "ToruAnno",
        "area": "annotation / review software",
        "text": "Built and maintained a multi-user computer-vision annotation and review platform on Cloudflare Workers, Supabase/Postgres/Auth, and R2, with reviewer queues, edit locks, minor-version history, resumable imports, reproducible training exports, aggregate dashboards, and concurrent-save protections."
      },
      {
        "name": "Production debugging",
        "area": "correctness / performance",
        "text": "Tracked issues around image navigation, saves, locks, duplicate metadata, prefetching, dashboard cost, access control, and observability with layer-by-layer measurement, request IDs, failure classes, targeted fixes, and path-level verification."
      },
      {
        "name": "Anarchyc",
        "area": "shared gpu coordination",
        "text": "Built a shared EC2/GPU coordination service with a realtime fleet dashboard, Python CLI, stable identity, token-scoped actions, waiting queues, and declared usage so people and coding agents could avoid stepping on each other."
      },
      {
        "name": "Shared context tooling",
        "area": "agent tooling",
        "text": "Built shared-context tooling for coding-agent work with append-only records, namespaces, verified handoffs, secret rejection, REST/MCP surfaces, export/restore, and recovery paths for long-running tasks where memory drift creates real bugs."
      },
      {
        "name": "SheetScanner",
        "area": "document software",
        "text": "Worked on Android bulk answer-sheet capture with CameraX preview, analysis, and capture; automatic page detection; ONNX document-corner inference; quality gates; page-turn/re-arm logic; batch resume; raw JPEG storage; and JSON/EXIF capture metadata."
      },
      {
        "name": "Model lifecycle work",
        "area": "training / evaluation",
        "text": "Used reviewed datasets, detector training and comparison, source-separated evaluation, visual checks, leakage gates, frozen tests, and comparative benchmarks to guide model promotion and stop decisions."
      }
    ]
  },
  "projects": {
    "featured": [
      {
        "id": "concize",
        "name": "Concize",
        "type": "realtime audio",
        "product": "Concize is a meeting workspace for Indian-language and code-mixed calls. It turns live meeting audio into searchable timelines, cited answers, and follow-up context.",
        "implementation": "The current path uses authenticated WebSockets, separate transcription and speaker lanes, a sequence-derived session clock, append-only Postgres revisions, deterministic chunks, Postgres lexical search, Qdrant dense retrieval, and SSE cited chat.",
        "ownership": "Co-developed · backend by me",
        "stack": [
          "Node.js",
          "TypeScript",
          "WebSockets",
          "PostgreSQL",
          "Supabase",
          "Qdrant",
          "Redis",
          "RabbitMQ sidecar",
          "Python services"
        ],
        "flow": [
          "browser audio",
          "WebSocket lanes",
          "revisioned transcript",
          "Postgres + Qdrant",
          "cited chat"
        ],
        "source": "https://github.com/rx6ru/Concize/tree/v4",
        "live": null,
        "mark": "concize",
        "markImage": "https://rxbru.vercel.app/images/projects/concize-icon.webp",
        "visual": "https://rxbru.vercel.app/images/artifacts/project-concize.webp"
      },
      {
        "id": "trecl",
        "name": "Trecl",
        "type": "agent workflow",
        "product": "Trecl is a company-research agent for targeted outreach. It studies a company, finds useful openings or OSS angles, waits for human target selection, and drafts outreach without auto-sending anything.",
        "implementation": "A LangGraph fan-out/fan-in sends web research into Qdrant, runs parallel job and GitHub branches, lets a curator rank targets, preserves the human pause in SQLite, and keeps the isolated ReAct GitHub path behind tool and input guardrails.",
        "ownership": "Solo",
        "stack": [
          "Python",
          "LangGraph",
          "SQLite",
          "Qdrant",
          "PyGitHub",
          "Pydantic"
        ],
        "flow": [
          "ingest",
          "parallel job analysis",
          "GitHub analysis",
          "human selection",
          "draft"
        ],
        "source": "https://github.com/rx6ru/Trecl",
        "live": null,
        "mark": "dag",
        "markImage": "https://rxbru.vercel.app/images/projects/trecl-mark.webp",
        "visual": "https://rxbru.vercel.app/images/artifacts/project-trecl.webp"
      },
      {
        "id": "icberg",
        "name": "IcBerg",
        "type": "data analysis",
        "product": "IcBerg is a safety layer between AI agents and databases. It reviews proposed SQL, blocks risky actions, routes approval-worthy changes to a human, and allows bounded read-only analysis when the policy permits it.",
        "implementation": "The system uses sqlglot recursive classification across reads, writes, DDL, CTEs, and subqueries; fail-safe policy decisions; least-privilege reads; PII redaction; approval-gated writes; hash-chained audit; and SDK, REST-SSE, MCP, and LangGraph surfaces.",
        "ownership": "Solo",
        "stack": [
          "Python",
          "SQLGlot",
          "Policy engine",
          "PII redaction",
          "Hash-chained audit",
          "REST-SSE",
          "MCP",
          "LangGraph"
        ],
        "flow": [
          "SQL proposal",
          "classify risk",
          "policy gate",
          "approval or read path",
          "audit event"
        ],
        "source": "https://github.com/rx6ru/IcBerg",
        "live": null,
        "mark": "iceberg",
        "markImage": "https://rxbru.vercel.app/images/projects/icberg-mark.webp",
        "visual": "https://rxbru.vercel.app/images/artifacts/project-icberg.webp"
      },
      {
        "id": "strata",
        "name": "Strata",
        "type": "agent memory",
        "product": "Strata is a portable memory system for coding agents. It gives agents and humans one durable project record without mixing namespaces, leaking secrets, or rewriting history.",
        "implementation": "It uses append-only records, schema and policy checks, content hashes, namespaces, secret rejection, supersede/relocate/split/merge events, export/restore, and CLI, REST, MCP, and skill-pack surfaces for verified handoffs.",
        "ownership": "Solo",
        "stack": [
          "Python",
          "MCP",
          "REST",
          "Append-only records",
          "Policy checks",
          "Agent context",
          "Verification checks"
        ],
        "flow": [],
        "source": "https://github.com/rx6ru/strata",
        "live": null,
        "mark": "layers",
        "markImage": "https://rxbru.vercel.app/images/projects/strata-mark.webp",
        "visual": "https://rxbru.vercel.app/images/artifacts/project-strata.webp"
      }
    ],
    "additional": [
      {
        "name": "Wombat",
        "ownership": "Co-developed · backend/security by me",
        "product": "Wombat is an API-key vault for teams that need scoped access without exposing raw provider secrets. It handles ownership checks, encrypted storage, rate limits, validation, and documented API contracts.",
        "source": "https://github.com/rx6ru/Wombat",
        "logo": "https://rxbru.vercel.app/images/projects/wombat-mark.webp",
        "logoKind": "mark"
      },
      {
        "name": "Saturday",
        "ownership": "Co-developed",
        "product": "Saturday is a voice search tool for codebases. It indexes a repository, connects a voice assistant to a local webhook, and lets a developer ask spoken questions while working.",
        "source": "https://github.com/rx6ru/Saturday",
        "logo": "https://rxbru.vercel.app/images/projects/saturday-wordmark.webp",
        "logoKind": "wordmark"
      },
      {
        "name": "Reclaym",
        "ownership": "Solo",
        "product": "Reclaym is a UPI AutoPay recovery engine for failed subscription payments. It receives payment events, deduplicates retries, applies deterministic recovery policy, and reconciles payment-state changes.",
        "source": "https://github.com/rx6ru/Reclaym",
        "logo": "https://rxbru.vercel.app/images/projects/reclaym-mark.webp",
        "logoKind": "mark"
      },
      {
        "name": "Headless Ghidra MCP",
        "ownership": "Co-developed",
        "product": "Headless Ghidra MCP is a native inspection bridge for reverse-engineering workflows. It exposes Ghidra analysis, decompilation, imports, exports, call graphs, JSON output, pagination, caching, and safer path handling.",
        "source": "https://github.com/QuiteArpit/HeadlessGhidraMCP",
        "logo": "https://rxbru.vercel.app/images/projects/headless-ghidra-mark.webp",
        "logoKind": "mark"
      }
    ]
  },
  "toolkit": [
    {
      "title": "Backend and APIs",
      "note": "Service boundaries, authentication, realtime delivery, and documented contracts.",
      "skills": [
        "Python",
        "TypeScript",
        "Node.js",
        "Express.js",
        "FastAPI",
        "REST",
        "WebSockets",
        "SSE",
        "JWT/JWKS",
        "OpenAPI"
      ]
    },
    {
      "title": "Data, state, and storage",
      "note": "Durable state, queues, retrieval, and consistency under concurrent work.",
      "skills": [
        "PostgreSQL",
        "Supabase",
        "Redis",
        "MongoDB",
        "SQLite",
        "Prisma",
        "Qdrant",
        "RabbitMQ",
        "row-level locking",
        "idempotency"
      ]
    },
    {
      "title": "Reliability and verification",
      "note": "Production diagnosis, observability, automated tests, and evidence-driven evaluation.",
      "skills": [
        "Sentry",
        "request tracing",
        "structured logs",
        "pytest",
        "Jest/Vitest",
        "benchmarks",
        "baselines",
        "retry/backoff",
        "audit logs",
        "leakage checks"
      ]
    },
    {
      "title": "Cloud and tooling",
      "note": "Edge and cloud runtimes, object storage, deployment, and operator tooling.",
      "skills": [
        "Cloudflare Workers",
        "Cloudflare R2",
        "Durable Objects",
        "AWS EC2/S3",
        "Docker",
        "GitHub Actions",
        "Linux",
        "Git",
        "Python CLIs",
        "Vercel"
      ]
    },
    {
      "title": "Applied AI systems",
      "note": "Retrieval, agents, speech and document pipelines, and model evaluation inside products.",
      "skills": [
        "RAG",
        "LangGraph",
        "MCP",
        "structured outputs",
        "multi-provider routing",
        "LangSmith tracing",
        "STT/OCR pipelines",
        "RF-DETR",
        "ONNX Runtime",
        "model evaluation",
        "prompt-injection checks"
      ]
    }
  ],
  "activity": {
    "name": "Coding activity",
    "description": "Terminal-style seven-day coding activity snapshot.",
    "source": "WakaTime",
    "liveSection": "https://rxbru.vercel.app/#activity",
    "freshness": "Dynamic. Fetch the live portfolio for current totals, languages, and editors; do not treat cached fallback values as permanent profile facts.",
    "fallback": {
      "usedWhen": "WakaTime is unavailable or the seven-day total is below 3600 seconds.",
      "meaning": "Default activity distribution used when live seven-day data is unavailable or too sparse to be representative.",
      "languages": [
        {
          "name": "Python",
          "percent": 48
        },
        {
          "name": "TypeScript",
          "percent": 27
        },
        {
          "name": "Bash",
          "percent": 10
        },
        {
          "name": "Rust",
          "percent": 7
        },
        {
          "name": "Markdown",
          "percent": 5
        },
        {
          "name": "Git Config",
          "percent": 3
        }
      ],
      "editors": [
        {
          "name": "Zed",
          "percent": 95
        },
        {
          "name": "Cursor",
          "percent": 5
        }
      ],
      "os": "Arch Linux (Kernel 6.8.9)"
    }
  },
  "contact": {
    "email": "amarmahato.cs@gmail.com",
    "github": "https://github.com/rx6ru",
    "linkedin": "https://www.linkedin.com/in/rxbru/",
    "resume": "https://rxbru.vercel.app/Amar_Mahato_Software_Engineer.pdf",
    "links": [
      {
        "label": "Email",
        "value": "amarmahato.cs@gmail.com",
        "href": "mailto:amarmahato.cs@gmail.com"
      },
      {
        "label": "GitHub",
        "value": "github.com/rx6ru",
        "href": "https://github.com/rx6ru"
      },
      {
        "label": "LinkedIn",
        "value": "linkedin.com/in/rxbru",
        "href": "https://www.linkedin.com/in/rxbru/"
      }
    ]
  },
  "portfolioSite": {
    "stack": [
      "Next.js",
      "React",
      "TypeScript"
    ],
    "design": {
      "direction": "Editorial software-engineering portfolio with modern startup motion and restrained technical typography.",
      "themes": [
        "light",
        "dark"
      ],
      "primaryAccent": "cobalt blue",
      "hero": "Animated cloudy field with theme-aware fallback rendering and a blended text edge.",
      "projectPresentation": "Product-first summaries with clickable disclosures, source actions, project marks, and generated visual banners."
    },
    "interfaceFeatures": [
      "light and dark themes",
      "responsive 360px, 390px, and 430px layouts",
      "animated cloudy hero artwork with fallback rendering",
      "native-cursor ASCII motion effect on supported desktop pointers",
      "clickable Work and Project disclosures",
      "direct project source links",
      "CV, GitHub, LinkedIn, and email actions"
    ],
    "machineReadableEndpoints": {
      "llms": "https://rxbru.vercel.app/llms.txt",
      "llmsFull": "https://rxbru.vercel.app/llms-full.txt",
      "llmCompatibility": "https://rxbru.vercel.app/llm.txt",
      "markdownOverview": "https://rxbru.vercel.app/index.md",
      "workMarkdown": "https://rxbru.vercel.app/work.md",
      "projectsMarkdown": "https://rxbru.vercel.app/projects.md",
      "skillsMarkdown": "https://rxbru.vercel.app/skills.md",
      "answersMarkdown": "https://rxbru.vercel.app/answers.md",
      "resumeMarkdown": "https://rxbru.vercel.app/resume.md",
      "json": "https://rxbru.vercel.app/portfolio.json",
      "sitemap": "https://rxbru.vercel.app/sitemap.xml",
      "robots": "https://rxbru.vercel.app/robots.txt",
      "humans": "https://rxbru.vercel.app/humans.txt",
      "manifest": "https://rxbru.vercel.app/manifest.webmanifest",
      "shareImage": "https://rxbru.vercel.app/opengraph-image",
      "twitterImage": "https://rxbru.vercel.app/twitter-image"
    }
  },
  "interpretation": {
    "attribution": [
      "Concize is co-developed; Amar's verified public role is backend ownership.",
      "Trecl, IcBerg, and Strata are presented as solo projects.",
      "Wombat is co-developed; Amar's public role is backend and security.",
      "Saturday and Headless Ghidra MCP are co-developed.",
      "Reclaym is presented as a solo additional build, not a featured project."
    ],
    "sourcePolicy": "Public repositories and the public resume are the implementation references. Employer-private datasets, URLs, credentials, account identifiers, internal metrics, and other non-public material are intentionally excluded."
  },
  "faq": [
    {
      "question": "Who is Amar Mahato?",
      "answer": "Amar Mahato is a software engineer in India focused on backend systems and applied AI. His work emphasizes APIs, realtime systems, databases and state, reliability, retrieval, cloud tooling, model evaluation, and agent workflows."
    },
    {
      "question": "What kind of engineer is Amar?",
      "answer": "His durable positioning is Software Engineer, with Backend Systems + Applied AI as the specialization. AI is one layer in the systems he builds rather than the entire product identity."
    },
    {
      "question": "What are Amar's primary languages?",
      "answer": "Python and TypeScript are the primary implementation languages. JavaScript and SQL also appear in the public resume and repository evidence."
    },
    {
      "question": "What did Amar build at IntelGrader?",
      "answer": "The public portfolio describes a multi-user computer-vision annotation and review platform, production debugging and reliability work, a shared EC2/GPU coordination service named Anarchyc, shared-context tooling for coding agents, sanitized Android document-capture work, and model lifecycle evaluation."
    },
    {
      "question": "What is Concize?",
      "answer": "Concize is a meeting workspace for Indian-language and code-mixed calls. It turns live audio into searchable timelines, cited answers, and follow-up context. Amar co-developed it and owns the backend work represented in the portfolio."
    },
    {
      "question": "What is Trecl?",
      "answer": "Trecl is a company-research agent for targeted outreach. It researches a company, finds job or open-source angles, pauses for human target selection, and drafts outreach without auto-sending."
    },
    {
      "question": "What is IcBerg?",
      "answer": "IcBerg is a safety layer between AI agents and databases. It classifies proposed SQL, blocks risky operations, routes approval-worthy changes to a human, permits bounded reads, redacts sensitive output, and records auditable decisions."
    },
    {
      "question": "What is Strata?",
      "answer": "Strata is portable memory infrastructure for coding agents. It keeps project context durable, namespaced, reversible, secret-aware, and transferable across humans, agents, sessions, and machines."
    },
    {
      "question": "What backend and cloud technologies does Amar use?",
      "answer": "The public evidence includes Node.js, Express.js, FastAPI, REST, WebSockets, SSE, PostgreSQL, Supabase, Redis, MongoDB, SQLite, Prisma, Qdrant, RabbitMQ, Cloudflare Workers, Cloudflare R2, Durable Objects, AWS EC2/S3, Docker, GitHub Actions, Linux, Git, and Vercel."
    },
    {
      "question": "What reliability and evaluation work does Amar do?",
      "answer": "The portfolio lists production diagnosis, Sentry, request tracing, structured logs, pytest, Jest/Vitest, benchmarks, baselines, retry/backoff, audit logs, leakage checks, and model evaluation."
    },
    {
      "question": "What does the Coding activity section show?",
      "answer": "It is a terminal-style, seven-day coding snapshot sourced from WakaTime through the portfolio API. When the current week is empty or extremely low, it uses Amar's default distribution: Python, TypeScript, Bash, Rust, Markdown, then Git Config; Zed is the dominant editor with occasional Cursor use."
    },
    {
      "question": "How can someone contact Amar or view his resume?",
      "answer": "Email amarmahato.cs@gmail.com, use the LinkedIn or GitHub links, or open the public resume at https://rxbru.vercel.app/Amar_Mahato_Software_Engineer.pdf."
    }
  ]
}