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SushP07/README.md
Professional Header

Sushrut Pakhale

Senior Software Engineer | Research Infrastructure & AI Systems | Leamington Spa, UK

Building resilient, production-grade systems that bridge infrastructure engineering with cutting-edge AI research.

LinkedIn GitHub Portfolio Email


🎯 Professional Overview

Senior Software Engineer with 4+ years of production experience designing scalable infrastructure, data pipelines, and AI-orchestrated systems. Specialized in research software engineering, multi-provider LLM systems, and production reliability.

Key Impact:

  • Architected enterprise infrastructure supporting 200+ repositories and 50+ teams
  • Resolved 132 production incidents in one year with ~1 hour MTTR
  • Reduced deployment lead time by 35% through CI/CD automation
  • Achieved 99%+ uptime on critical multi-provider LLM orchestration systems

πŸ’Ό Core Expertise

Area Technologies & Specializations
Languages & Frameworks Python 3.11+ β€’ FastAPI β€’ C# β€’ TypeScript β€’ SQL
AI & LLM Systems Multi-provider LLM orchestration β€’ Gemini API β€’ Groq β€’ Agno framework β€’ RAG β€’ Fine-tuning
Cloud & Infrastructure AWS (EC2, Lambda, S3) β€’ Azure (AKS, Functions, Monitor) β€’ Kubernetes β€’ Terraform β€’ GitHub Actions
Data Engineering Databricks (PySpark) β€’ Snowflake β€’ PostgreSQL β€’ Real-time ingestion β€’ Anomaly detection
DevOps & Reliability CI/CD automation β€’ Infrastructure-as-Code β€’ Monitoring (Prometheus/Grafana) β€’ Incident response
Software Design SOLID Principles β€’ Design Patterns (Facade, Component Isolation) β€’ System architecture β€’ Testing

πŸš€ Featured Project: AI News Synthesizer

Production research pipeline ingesting 200+ RSS feeds with multi-provider LLM orchestration and intelligent temporal windowing.

Key Features:

  • Resilience: Gemini primary + Groq fallback with 3-retry exponential backoff β†’ 99%+ uptime
  • Data Integrity: Strict error handling ensuring visible failures for research reproducibility
  • Temporal Intelligence: Dynamic gap calculation (T-1 to T-118 days) for catch-up scenarios
  • Quality: 5 unit tests β€’ ~75% code coverage β€’ Comprehensive production documentation
  • Automation: GitHub Actions CI/CD with scheduled daily execution and manual triggers

Repository: github.com/SushP07/ai-news-synthesizer


πŸ“Š Professional Metrics

Metric Value
Years of Production Experience 4+ years
Teams Supported 50+ engineering teams
Infrastructure Scale 200+ repositories
Production Incidents Resolved 132 (past year)
Mean Time to Resolve ~1 hour
CI/CD Lead Time Reduction 35%
System Uptime (Critical Systems) 99%+
Code Coverage (Research Projects) ~75%
Automated Data Validation 91%

πŸŽ“ Education & Certifications

MSc Applied Artificial Intelligence | Cranfield University (2021-2022)

  • Surpassed state-of-the-art benchmarks on FOD-A dataset using BYOL

BSc Computer Science | Rashtrasant Tukdoji Maharaj Nagpur University (2017-2021)

AWS Certified AI Practitioner (2023)
Databricks Generative AI Fundamentals (2024)


πŸ“ˆ GitHub Activity

GitHub Stats Top Languages


πŸ”— Quick Links


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