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About Baber
Baber Javed is a Senior AI Engineer and technology entrepreneur specializing in production-grade AI agents, LLM applications, and intelligent automation. He is the Founder and CEO of Square63, a software engineering company established in 2011.
Baber has hands-on experience designing and deploying agentic AI systems using Python, FastAPI, LangChain, LangGraph, OpenAI, Azure OpenAI, RAG, Qdrant, LanceDB, PostgreSQL, and Redis. His work spans multi-agent workflows, tool calling, retrieval pipelines, persistent conversational memory, AI evaluation, and real-time voice and messaging applications.
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As a Founding AI Engineer at GetAddie, he built production AI college-counseling systems operating across web, SMS, and real-time voice, including stateful LangGraph workflows, retrieval and ranking pipelines, and tool-enabled AI agents.
He also works on AI reliability and evaluation, with a focus on testing production agents for hallucinations, tool misuse, unsupported decisions, retrieval failures, security issues, and human-escalation gaps.
Baber combines deep software engineering experience with practical AI product development, helping startups and businesses turn LLM capabilities into reliable, production-ready systems.
Professional profile
- Location
- Pakistan
- Time zone
- Asia/Karachi
- Work mode
- Remote, Hybrid, On-site
- Availability
- Available Now
- Languages
- English
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Proven on the network
Implementation records and publicly available work, where published.
0 AI Deployments delivered. No publicly identified implementations are available to inspect.
03
What Baber builds
Implementation domains listed on this profile. Evidence-supported items are identified separately below.
Specialisations
AI Agents
AI Evaluation & Testing
Conversational AI
Multi-Agent Systems
RAG & Knowledge Retrieval
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AI Deployments
Real AI implementations demonstrated through evidence.
No publicly identified Deployments are available to inspect.
05
Implementation capabilities
Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.
Evidence-supported
No published evidence linked yet.
Builder declared
- AI Agents
- AI Evaluation & Testing
- Conversational AI
- Multi-Agent Systems
- RAG & Knowledge Retrieval
06
Technology
Technologies listed by the Builder, distinguished by published evidence.
Evidence-supported
No published evidence linked yet.
Builder declared
- Amazon Bedrock
- Claude Agent SDK
- FastAPI
- LangChain
- LangGraph
- OpenAI Agents SDK
- Python
07
Industry experience
Published Deployments support the listed counts. Other industries are Builder declared.
Accounting & Audit
Builder declared
E-Commerce
Builder declared
Education
Builder declared
Hospitality & Travel
Builder declared
Software & SaaS
Builder declared
08
Trust & verification
A closer look at how this profile and its evidence are reviewed.
Community Member
Published evidence is reviewed against the AI Deploy Network Evidence Standard.
How verification works
Verified Builder
Independently reviewed by AI Deploy Labs against the platform Evidence Standard.
How this is verifiedWhat the platform has established, and what remains builder-declared.
- Identity and organisation
- Identity checks confirm that the person presenting this profile controls the account and the professional identifiers attached to it, such as a LinkedIn profile. Organisation membership is confirmed by the organisation, not self-declared by the builder.
- AI Deployments
- An approved AI Deployment is an implementation record the builder submitted and the platform reviewed against the Evidence Standard before publication. Approval confirms the record is complete, coherent and consistent with the supporting material provided — it is not an audit of the client's systems.
- Business outcomes
- Outcome figures are recorded by the builder on the deployment or case study that produced them, and are reviewed at publication. Aggregates shown on this profile are calculated from those approved records only.
- Evidence
- Supporting evidence comes from the records the builder published on this platform: approved AI Deployments, published AI Case Studies, verification outcomes and organisation participation.
- Currency
- Older evidence continues to count and is never removed. Recency is presented separately through Professional Currency so that current expertise can be assessed alongside historical work.
- Traceability
- Every figure on this profile can be followed to the record that produced it. Open the linked AI Deployment or AI Case Study to read the outcome exactly as it was reported.
The platform does not independently audit client systems or financial records. How this is verified
Professional record and further evidence
Client Portfolio
Portfolio started
Rotobot
Agentic AI • Sports & Events
United States2025Built an AI-powered fantasy football analytics platform using GPT-4, Qdrant vector search, and SQL-based data querying. Developed intelligent data retrieval and analysis workflows that enabled users to ask questions and receive contextual, data-driven insights.
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