Toronto, Canada · AI / Full-Stack Engineering

Sri Ranga Bharadwaj Chakilam

Senior AI Engineerbuilding production AI systems.

Current proofCurrently building enterprise document-processing workflows at Fisent Technologies across classification, extraction, validation, orchestration, and monitoring.

Backend-focused AI engineer building agent workflows, APIs, data platforms, and cloud-native product systems for real users.

I work across model orchestration, service boundaries, persistence, observability, and product interfaces so AI features stay reliable after launch.

Agentic AILLMsBackend SystemsAWSPostgreSQL

View engineering work GitHub

Selected systems

Engineering work with product depth.

Flagship projects are presented as architecture and engineering case studies. Production source stays private where exposing implementation would create unnecessary product or security risk.

01Content sources

02AI workflow

03API services

04PostgreSQL

05AWS runtime

AI-powered technology media platform

TechBeetle

A production-oriented content platform combining AI-assisted editorial workflows with authenticated APIs, PostgreSQL-backed services, AWS infrastructure, CI/CD, and operational monitoring.

AI-assisted research, classification, generation, and publishing workflows
Modular backend APIs with authentication, rate limiting, and PostgreSQL persistence
AWS-based production architecture with observability and environment-aware delivery

01Statement upload

02Validation

03Reconciliation

04Verified facts

05Grounded insights

Financial data intelligence platform

CreditClarity

A secure statement-intelligence system exploring structured document processing, reconciliation, deterministic financial logic, and grounded AI narratives behind a production-shaped API architecture.

FastAPI services, relational data modeling, authentication, and protected document workflows
Statement extraction and reconciliation with confidence-aware review patterns
Grounded AI design where generated insights are constrained by verified application facts

Engineering capabilities

AI is one layer of the system — not the whole system.

I work across model workflows, backend services, data systems, cloud infrastructure, and product interfaces so AI features can operate reliably in production.

AI Engineering

Designing reliable AI features that operate inside real application workflows.

LLM applicationsAgentic workflowsRAGEvaluationsGuardrailsHuman-in-the-loop

Backend Systems

Building APIs and services with clear boundaries, secure access, and durable data models.

PythonNode.jsFastAPIREST APIsAuthenticationPostgreSQL

AI / Data Platforms

Turning unstructured inputs and operational data into validated, observable workflows.

Document processingData qualityStructured pipelinesValidationObservabilityWorkflow orchestration

Cloud & Production

Treating deployment, monitoring, security, and failure modes as part of the system design.

AWSDockerCI/CDGitHub ActionsMonitoringProduction readiness

Engineering approach

Build AI around reliable systems, not the other way around.

Ground intelligence in data

Use structured facts, deterministic logic, validation, and traceability before generative output.

Design for production

Authentication, observability, failure modes, CI/CD, performance, and operational controls belong in the architecture.

Keep systems understandable

Maintain explicit boundaries between frontend, backend, AI, data, and infrastructure so systems remain testable and maintainable.

Selected experience

From AI workflows to production application delivery.

A concise view of the roles and product work most relevant to AI engineering, backend systems, and full-stack product development.

Jan 2024 — Present

Toronto, Ontario

Senior AI Engineer

Fisent Technologies

Building AI-powered document and records-processing workflows across classification, extraction, validation, orchestration, and operational monitoring.

Designed LLM and agent-based processing workflows using Python and orchestration frameworks
Integrated AI workflows with enterprise applications through APIs and cloud-native services
Built monitoring-oriented product experiences for AI outputs, exceptions, and processing state

PythonLangGraphLangChainReactAWSPostgreSQL

Jun 2023 — Dec 2024

Toronto, Ontario

AI Engineer / Full-Stack Developer

IvaTech Consulting

Delivered AI-enabled and full-stack application work spanning product interfaces, APIs, data workflows, deployment, and production reliability.

Built React/Next.js and backend application capabilities with API and database integration
Developed scalable backend patterns, authentication services, and data-driven workflows
Used CI/CD, containerization, logging, and performance analysis to improve delivery reliability

ReactNext.jsNode.jsPythonPostgreSQLDocker

Jan 2022 — May 2023 · continued independent development

Product / Independent

Founder · AI Engineer · Full-Stack Developer

TechBeetle

Created and evolved a technology media product into an AI-enabled, cloud-hosted application with modern frontend, backend, data, and operational capabilities.

Built AI-assisted editorial and content-processing workflows
Developed product interfaces, APIs, authentication, data services, and analytics capabilities
Modernized infrastructure, automated testing, CI/CD, and production monitoring

TypeScriptReactNode.jsPostgreSQLAWSOpenAI-compatible APIs

Selected AI / ML projects

Earlier model work that still shows useful engineering range.

These projects are intentionally secondary to the production-oriented systems above, but they demonstrate hands-on computer vision and ML application development.

Computer Vision / Deep Learning

Facial Expression Detection

Deep-learning project for facial-expression recognition and emotion classification, demonstrating model-driven product integration and computer-vision workflows.

PythonTensorFlowOpenCVCNNs

View repository

Computer Vision / Automation

MaskNotify

Computer-vision system for face-mask compliance detection and personalized alerting, built as a university engineering project.

PythonOpenCVTensorFlowKeras

View repository

Technology

A practical stack for AI-enabled product engineering.

Grouped by the role each technology plays in the system instead of presented as a badge wall.

AI

OpenAI APIsLLMsRAGAgentsLangGraphLangChainEvalsGuardrails

Languages & Backend

PythonTypeScriptJavaScriptNode.jsFastAPIDjangoREST APIs

Frontend

ReactNext.jsTailwind CSSAccessible UIResponsive product interfaces

Data

PostgreSQLSQLSupabaseRelational modelingDocument/data processing

Cloud & Delivery

AWSDockerGitHub ActionsCI/CDCloudWatchNetlifyVercel

Education

Software engineering foundation.

Conestoga College

Post-Graduate Diploma · Web Development

2021 — 2022Ontario, Canada

Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya

Bachelor of Engineering · Computer Science and Engineering

2016 — 2020India

Certifications

AWS Certified Cloud Practitioner

Microsoft Azure Fundamentals

Generative AI Professional Certification

Contact

Building an AI product or engineering team that values production quality?

I am interested in senior AI engineering, AI application engineering, backend/full-stack roles, and product collaborations where reliable systems matter as much as model capability.

Email LinkedIn GitHub