PRATHAMESH
BELVALKAR

Who am I

Solution Architect specializing in building scalable backend systems and high-performance web applications that align with business goals and deliver excellent user experiences.

Currently working as Assistant Solution Architect at Airrived AI.

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Architecture15 min read

Evaluating Tech and Assisting the Solution Architect

Vendors and frameworks arrive weekly in AI-heavy environments: a new vector database, a new gateway, a new “agent platform.” My job is not to chase novelty. It is to run evaluations that the Solution Architect can trust — evidence, risks, and a clear recommend/reject.

I decide small bets. I prepare large ones.

Hands comparing notes and diagrams while evaluating technical options

Taste selects candidates. Spikes select winners. Governance selects what we can live with.

| Decision type | Owner | Example | | --- | --- | --- | | Local pattern inside a service | ASA + service lead | Retry policy for one worker | | Cross-service contract | ASA recommends, SA confirms | Event schema for document ingested | | Vendor / compliance / multi-year bet | Solution Architect | Primary LLM vendor, data residency | | Emergency mitigation | On-call + ASA advisory | Temporary feature flag disable |

Clarity here prevents both paralysis and cowboy architecture.

stateDiagram-v2
    [*] --> CandidateList
    CandidateList --> SpikeDesign
    SpikeDesign --> BakeOff
    BakeOff --> RiskRegister
    RiskRegister --> Recommend
    Recommend --> SADecision
    SADecision --> AdrAccepted: accept
    SADecision --> Rejected: reject
    Rejected --> [*]
    AdrAccepted --> [*]

I never jump from a conference talk to production. The bake-off is where marketing claims go to die.

A spike needs:

Success criteria written before coding (latency, cost, ops burden, team skill)
Same workload for each option
Time box (often 2–3 days)
Honest failure — stopping early is a valid result

bake_off:
  subject: "Vector index for Northline Assist"
  workload:
    documents: 50_000
    avg_chunk_tokens: 400
    queries: 1_000
  criteria:
    - name: p95_query_ms
      target: 120
      weight: 0.35
    - name: reindex_minutes
      target: 30
      weight: 0.2
    - name: ops_complexity
      scale: 1-5
      weight: 0.25
    - name: monthly_cost_at_load
      weight: 0.2
  options:
    - pgvector_on_existing_postgres
    - managed_vector_service
  timebox_days: 3

If criteria appear after results, someone is rationalizing.

I keep memos short enough that the Solution Architect can read them between meetings:


### Why
Meets p95 on the bake-off workload, reuses ops knowledge, defers new vendor.

### Risks
Index bloat under heavy re-embed; need autovacuum playbook.

### When to revisit
Corpus > 5M chunks or multi-region active-active search.

### Rejected
Managed vector service — better scale story, higher ops + cost for current stage.

Then we cut an ADR. The memo is the pre-read; the ADR is the record.

I track risks as rows, not vibes:

type Risk = {
  id: string;
  description: string;
  likelihood: 1 | 2 | 3 | 4 | 5;
  impact: 1 | 2 | 3 | 4 | 5;
  mitigation: string;
  owner: string;
};

function score(r: Risk) {
  return r.likelihood * r.impact;
}

const risks: Risk[] = [
  {
    id: 'R-12',
    description: 'Provider region outage blocks completions',
    likelihood: 2,
    impact: 5,
    mitigation: 'Queue + degrade to retrieval-only mode flag',
    owner: 'asa',
  },
  {
    id: 'R-18',
    description: 'Vector reindex blocks writes',
    likelihood: 3,
    impact: 3,
    mitigation: 'Blue/green index alias swap',
    owner: 'devtools',
  },
];

const ordered = [...risks].sort((a, b) => score(b) - score(a));

High scores must appear in the design review, not in a private doc.

I bring options and a recommendation. I do not ambush the Solution Architect in a public forum with a surprise “we already chose.” If evidence changes after their decision, I propose a superseding ADR — I do not quietly reverse course in a PR.

Loyalty to the system means loyalty to the decision process.

Where recommendations become ADRs: Architecture Decision Records in Git. Cost criteria: NFRs, Effort, and Infrastructure Cost. Role context: From Engineer to Assistant Solution Architect. Ops reality checks: Docker in Production: Beyond the Basics.

Evaluate in the open. Decide with evidence. Support the Solution Architect by making the hard choice the clear choice.

Sep 15, 2026Read

About / Profile

Over the years, I have worked on end-to-end web applications with a strong focus on scalable architecture, secure API design, and seamless user experience

AI & Python Development

Backend Engineering

Say hello

prathameshbelvalkars@gmail.com

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AI and Python Developer with 2.5+ years of experience building intelligent backend systems, production-grade APIs, and automation workflows. Strong expertise in Python, SQL databases, authentication, and secure API design.

Experienced in AI integrations, real-time systems, and enterprise platforms. I prioritize building clean, maintainable codebases that enable continuous improvement, observability, and scalable delivery.

I hold a Master of Computer Applications (MCA) in Computer Science from KIT's IMER, Kolhapur, and a Bachelor of Computer Science from The New College, Kolhapur.

I am fluent in English, Hindi, and Marathi, with elementary proficiency in Japanese, and have experience working across diverse and collaborative teams.

Selected Experience

Airrived AI

Solution architecture and AI systems

Mar 2026 — Present

Produce architecture and data-flow diagrams, technical documentation, and architecture decisions; review designs and implementations; guide developers; partner with DevOps, product, and business teams.

Troubleshoot complex system-level problems; evaluate new technologies; estimate technical effort, infrastructure, and costs; assist the Solution Architect on larger decisions and ensure solutions meet business and technical requirements.

Position

Assistant Solution Architect

Location

India

Industry

Technology / AI

Website

airrived.ai

RaMee Systems Pvt. Ltd.

Enterprise software solutions

Feb 2025 — Feb 2026

Developed secure backend services and APIs with strong authentication and role-based access control, focused on reliability and performance.

Designed and optimized MySQL and PostgreSQL schemas for financial and operational systems, improving data integrity and reporting workflows.

Position

Software Engineer

Location

Pune (Aundh), India

Industry

Software

Website

rameesystems.com

NOITAVONNE INDIA

Full stack web application development

Aug 2023 — Feb 2025

Built enterprise applications and APIs, working with MongoDB and SQL databases for transactional and reporting systems.

Implemented authentication, authorization, and secure backend communication while optimizing services for scalability and reliability across multiple projects.

Position

Full Stack Developer

Location

Kolhapur, Maharashtra, India

Industry

Software

Website

noitavonne.com

Expertise & Capabilities

Specialized in the intersection of design precision and engineering excellence.

01 /

AI & Python Development

Building intelligent software solutions and AI-powered applications with Python, including solution architecture, C4 and data-flow diagrams, and architecture decisions.

Solution ArchitectureC4 / Data-flow DiagramsArchitecture Decision RecordsPythonAI IntegrationWebRTCWebSocket / RTMPREST APIs

02 /

Backend Engineering

Building performant, scalable backend systems and secure RESTful APIs, with design reviews, technical documentation, and effort estimation.

FastAPIDjangoSQLAlchemyCeleryJWT / RBACDesign ReviewsTechnical DocumentationEffort & Cost EstimationTechnology Evaluation

03 /

Frontend & Database

Crafting responsive interfaces and designing robust, optimized data layers.

ReactNext.jsTypeScriptJavaScriptReact QueryTailwind CSSReduxHTML5CSS3SassMySQLPostgreSQLMongoDBDockerGit

Connect

prathameshbelvalkars@gmail.com

LinkedIn GitHub

PRATHAMESHBELVALKAR

Who am I

About / Profile

Over the years, I have worked on end-to-end web applications with a strong focus on scalable architecture, secure API design, and seamless user experience

Selected Experience

Airrived AI

RaMee Systems Pvt. Ltd.

NOITAVONNE INDIA

Expertise & Capabilities

Specialized in the intersection of design precision and engineering excellence.

AI & Python Development

Backend Engineering

Frontend & Database

Connect

PRATHAMESH
BELVALKAR