Software engineer building practical AI agents, quantitative market tools, and resilient operational pipelines. Rooted in agriculture, driven by distributed systems and market mechanics.
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| MARKET MONITOR [LIVE] | Growing up around farming taught me that systems
| $AAPL ▲ 234.5 +1.8% | must be durable, low-maintenance, and built to
| $NVDA ▲ 128.2 +3.4% | survive harsh conditions. I bring that same
| $SPY ▼ 548.1 -0.4% | mindset to autonomous agents, logistics APIs,
|_________________________| and quantitative trading pipelines.
- Systematic Market Pipelines: Developing automated market data processing, daily streaming rebalancing, and quantitative signal smoothing with news factor analysis.
- Freight & Field Automation: Engineering real-world logistics tools and advisory platforms, integrating carrier load boards, mapping, and operational decision layers.
- Multi-Agent Orchestration: Designing autonomous developer agents and task orchestrators operating locally across WSL2 and Docker environments.
- Self-Hosted Infrastructure: Managing continuous mini-server stacks for edge container routing, telemetry, and energy grid monitoring.
- Core Languages: Python, TypeScript, SQL, Go, C++
- AI & Local Inference: Local LLMs (Qwen, DeepSeek-R1), Multi-Agent Pipelines, Function Calling, Prompt Optimization
- Backend & Systems: FastAPI, Next.js, PostgreSQL, Docker, Linux / WSL2, Redis
- Integrations & Data: Market Data APIs, Logistics APIs (DAT, Truckstop), Financial Telemetry Pipelines
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| "A tractor can't break down in the middle of harvest, |
| and an execution pipeline can't drop orders at the open.|
| Build deterministic, durable, and clean." |
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- LinkedIn: harkaranbrar7
- X: @harkaranbrar7
- GitHub: harkaranbrar7
Open to discussing systematic market systems, local AI agents, and practical automation.