Support and operations overload
Manual conversations, fractured tools, and repeated handoffs slow teams and reduce response quality.
I build AI systems that automate real business operations.
Current role
Lead Engineer at TalkifAI
Specialty
Voice AI, agentic workflows, RAG
Platform experience
LiveKit, SIP, FastAPI, Next.js
Best fit
Founders, startups, AI teams
Problems I Solve
I turn promising AI ideas into systems people can actually use.
The work is not only model calls. It is product thinking, backend architecture, workflow design, integrations, observability, and a user experience that makes AI feel dependable.
Explore ServicesAI prototypes that never scale
Without production architecture, workflows, and observability, promising AI proofs stall before launch.
Knowledge scattered across systems
Documents, tickets, and product data need to be connected into a trusted retrieval and answer pipeline.
Voice or chat experiences that feel brittle
Real conversations require stable audio, routing, state, and handoff logic, not just model responses.
What I Build
Production AI capabilities organized around business outcomes.
Voice AI Agents
Problem: Teams need AI that can speak with users, route calls, and handle real conversations.
Solution: I build low-latency voice systems with LiveKit, SIP/WebRTC, STT/TTS, Twilio, Telnyx, and backend orchestration.
Impact: Useful for support, booking, sales qualification, and internal voice workflows.
Agentic Workflows
Problem: Businesses want AI that can take action, not just answer questions.
Solution: I design tool-using agents with LangGraph, OpenAI SDK, MCP, APIs, checkpoints, and structured workflows.
Impact: Useful for automation, operations, customer success, and multi-step business processes.
RAG Knowledge Systems
Problem: Generic AI answers are not enough when decisions depend on trusted company knowledge.
Solution: I build retrieval systems, ingestion pipelines, context flows, and assistant experiences around real documents and data.
Impact: Useful for support copilots, internal knowledge assistants, and domain-specific product experiences.
Full Stack SaaS Platforms
Problem: AI products still need clean interfaces, reliable APIs, auth, data models, and deployment.
Solution: I ship product interfaces and backend systems with Next.js, TypeScript, FastAPI, PostgreSQL, Docker, and cloud services.
Impact: Useful for MVPs, dashboards, automation platforms, and production AI product foundations.
Featured Case Studies
Proof from AI products, voice infrastructure, and SaaS automation.
These projects show the shape of my work: translating messy business operations into useful AI systems with product interfaces, backend architecture, integrations, and deployment paths.
Founding team member and Lead Engineer
TalkifAI - Voice Agent Platform
Founding member of a no-code/developer platform for creating, deploying, and scaling AI voice agents with sub-second latency. Architected LiveKit + SIP infrastructure and built BYOC abstraction.
ChallengeCreate a platform foundation for deployable AI voice agents with telephony, realtime audio, and customer-facing workflows.
SolutionArchitected LiveKit and SIP infrastructure, BYOC telephony layers, backend services, and product workflows for agent deployment.
OutcomeA production-focused voice agent platform foundation for support, sales, and business automation use cases.
AI workflow and product engineer
Personal AI Employee (Digital FTE)
Autonomous 24/7 Digital FTE on Azure using Claude Code and MCP to monitor and execute actions across channels. Reduces cost per task significantly while ensuring 24/7 availability.
ChallengeDesign an autonomous digital worker that can monitor channels and take action across tools.
SolutionUsed Claude Code, MCP, Azure, and full stack orchestration to connect reasoning with operational workflows.
OutcomeA practical Digital FTE concept for always-on task execution and lower-cost operations.
Full stack and agentic systems engineer
AI-Powered Todo App with MCP
Fullstack web app with stateless AI chat interface using MCP tools for natural language task management. Built with FastAPI, SQLModel, and Neon PostgreSQL.
ChallengeMake task management usable through natural language while keeping business data structured and reliable.
SolutionBuilt a full stack MCP-powered todo app with FastAPI, SQLModel, Neon PostgreSQL, and a stateless AI chat interface.
OutcomeA clear example of how agentic interfaces can operate against real application data.
Full stack developer
Amazon Listing Automation
End-to-end pipeline from image upload to live Amazon listing with AI content generation.
ChallengeReduce manual work in Amazon listing creation, image handling, and product content generation.
SolutionBuilt automation flows for AI content generation, mockup processing, and Amazon SP-API listing workflows.
OutcomeA full stack automation product that turns repeated ecommerce operations into a guided workflow.
Technical Capabilities
A capability map for AI products, voice systems, and product-ready SaaS.
These are the engineering domains I combine to ship practical agentic AI work: from backend architecture and voice infrastructure to trustable knowledge retrieval and customer-facing product flows.
Core Stack
Next.js + FastAPI
Frontend, APIs, dashboards, and production web apps.
AI Focus
Agents + Voice
LangGraph, MCP, LiveKit, SIP, and RAG workflows.
Shipping Style
Product-minded
Clean UX, SEO, automation, and reliable deployment.
Frontend Engineering
Building responsive, production-quality interfaces with a focus on clarity, accessibility, and performance.
Next.js 16ReactTypeScriptJavaScriptTailwind CSSFramer Motion
• App Router architecture
• Responsive dashboards
• SEO-ready pages
• Accessible UI patterns
Backend & APIs
Designing backend systems that support AI products, SaaS workflows, and data-driven applications.
PythonFastAPINode.jsREST APIsSQLModelPostgreSQL
• API design
• Database modeling
• Background workflows
• Integration services
Agentic AI
Creating agents that use tools, follow workflows, retrieve knowledge, and operate across real systems.
LangGraphLangChainOpenAI SDKMCP ServersRAGMulti-agent Systems
• Tool-calling agents
• Multi-step workflows
• RAG pipelines
• Evaluation-aware design
Voice AI Infrastructure
Engineering real-time voice experiences with telephony, streaming, and conversational AI pipelines.
LiveKitSIPWebRTCTwilioTelnyxSTT/TTS Pipelines
• Low-latency voice flows
• BYOC telephony
• SIP routing
• Conversation pipelines
Cloud & Data
Shipping reliable applications with practical deployment, storage, and operational foundations.
DockerGoogle CloudMongoDBPostgreSQLNeonKubernetes
• Containerized services
• Cloud deployment
• Data persistence
• Scalable foundations
Product & Growth
Connecting technical implementation with product outcomes, search visibility, and user workflows.
Agentic SEOTechnical SEOSchema.orgProduct ThinkingDocumentationAI UX
• AI-readable content
• Metadata strategy
• Product clarity
• Documentation systems
Services
Focused AI engineering offers for teams that need production outcomes.
I work best where AI meets real operations: workflows, voice, tools, knowledge, product interfaces, APIs, and deployment.
Voice AI Agent Build
Best for
Support, sales, booking, and phone-based workflows
Deliverables
- LiveKit/SIP voice pipeline
- Telephony integration
- Agent flow and backend APIs
A voice experience that can talk to users, access business context, and route work reliably.
Agentic Workflow Automation
Best for
Teams replacing repetitive internal work with tool-using agents
Deliverables
- LangGraph/OpenAI workflow
- MCP or API tools
- Human checkpoints and logs
An AI workflow that plans, calls tools, updates systems, and stays understandable to operators.
RAG Knowledge Assistant
Best for
Products and teams with documents, policies, product data, or support knowledge
Deliverables
- Ingestion pipeline
- Retrieval strategy
- Chat or workflow interface
AI answers grounded in trusted data instead of generic model memory.
Full Stack AI SaaS MVP
Best for
Founders who need a product interface and backend around an AI workflow
Deliverables
- Next.js interface
- FastAPI backend
- Database, auth, deployment path
A usable product foundation that can be tested with customers and extended over time.
AI Integration Layer
Best for
Businesses connecting AI to CRMs, databases, dashboards, and third-party tools
Deliverables
- API/webhook integration
- Background jobs
- Data and action workflow
AI that can operate inside existing systems instead of sitting in a separate chat window.
Agentic SEO and AI Visibility
Best for
Technical brands and portfolios that need search and AI-agent readability
Deliverables
- Metadata and schema
- llms.txt strategy
- Crawlable content architecture
A clearer entity footprint for search engines, AI summarizers, and high-intent visitors.
Experience
Technical ownership across AI products and full stack systems.
I build the infrastructure, workflows, APIs, and interfaces that make AI systems dependable, scalable, and useful for operations.
July 2024 – Present
COO & Lead Engineer
TalkifAI
Founding member building a no-code voice agent platform. Architected self-hosted LiveKit + SIP on GCP. Built BYOC layer, Batch Calling, and automated RAG Knowledge Base indexing.
Designed the core voice-agent platform with LiveKit, SIP, and low-latency telephony.
Built BYOC telephony routing, batch calling, and automated RAG knowledge-base indexing.
Owned product implementation as a founding team member across architecture, backend, and workflows.
May 2025 – Jan 2026
Full Stack Developer
XponentialAI
Built JungleMug, an end-to-end Amazon listing automation platform. Integrated AI content generation, automated Photoshop scripting for mockups, and Amazon SP-API for direct listings.
Built JungleMug, an Amazon listing automation platform with AI-generated content and mockup workflows.
Integrated Amazon SP-API and automated product publishing across a full stack application.
Delivered frontend, backend, and operational systems that turned manual ecommerce work into a product workflow.
Credentials
Credentials that back the product and technical systems I build.
Certifications support the work, but the strongest signal is the architecture, deployment, and product execution behind the projects.
Certified Agentic AI Engineer
Intensive curriculum covering LLMs, RAG pipelines, multi-agent systems, and cloud deployment.
Certified Prompt & Context Engineer
Mastered prompt engineering, context engineering, and RAG pipelines.
FAQ
Questions clients usually ask before working together.
What types of AI systems do you build?
I build agentic workflows, voice AI agents, RAG knowledge systems, AI integrations, internal automation tools, and full stack SaaS products around AI use cases.
Can you handle both frontend and backend work?
Yes. My common stack includes Next.js, React, TypeScript, FastAPI, PostgreSQL, Docker, cloud deployment, APIs, and AI orchestration tools.
Do you work with founders and startups?
Yes. The portfolio is focused on founders, AI startups, SaaS teams, and technical teams that need practical product execution rather than only prototypes.
What makes your voice AI work different?
I have hands-on platform experience with LiveKit, SIP/WebRTC, BYOC telephony, Twilio, Telnyx, backend orchestration, and real-time agent workflows.
What is the best way to start a project conversation?
Send a short project brief through LinkedIn, Upwork, or email with the business goals, users, and systems you want to connect.
Work With Me
Have an AI workflow, voice agent, or SaaS product to build?
Share the business problem, the users, and the systems involved. I can help shape the architecture and build the product path from prototype to production-ready implementation.