.png){kind=logo}
Vetted Alerting Professionals
Pre-screened and vetted.
Junior Machine Learning Engineer specializing in LLMs and retrieval-augmented generation
Mid-level Full-Stack Software Engineer specializing in streaming media and real-time systems
Senior Backend Software Engineer specializing in Python and AWS cloud services
Senior Cloud Infrastructure & DevOps Engineer specializing in AWS, Kubernetes, and automation
Mid-level Software Engineer specializing in backend microservices and workflow automation
Mid-level Backend Software Engineer specializing in cloud databases
Senior QA Engineer specializing in AAA game quality engineering and Unreal Engine validation
Senior Machine Learning Engineer specializing in GenAI, NLP, and MLOps
Staff Software Engineer specializing in cloud, networking, and distributed systems
Mid-level Full-Stack Developer specializing in cloud-native apps, AI/ML, and microservices
Senior DevOps Engineer specializing in cloud infrastructure, Kubernetes, and CI/CD automation
Mid-level Data Engineer specializing in cloud lakehouse platforms (Azure/AWS/Snowflake)
Senior Software Engineer specializing in cloud-native healthcare and financial services
Senior Software Engineer specializing in DevSecOps and Azure cloud infrastructure
Mid-level Software Engineer specializing in backend systems and FinTech
Principal Software Engineer specializing in distributed systems and cloud microservices
Poorna Pedapudi
Mid-Level Software Engineer specializing in distributed backend systems and cloud-native microservices
“Software engineer focused on data platforms and applied LLM systems: built an internal data quality monitoring layer to catch silent data drift and iterated post-launch after finding ~30% false-positive alerts, reducing noise via dynamic baselines and improved structured logging. Also shipped a production RAG-based internal knowledge assistant over Jira/Confluence with citations, confidence-based fallbacks, and nightly automated evals to prevent regressions.”
Jiacheng Yin
Intern software engineer specializing in AI, backend systems, and cloud infrastructure
“Backend/AI systems engineer who has shipped production LLM agents focused on prompt engineering, code generation, and incident-response automation. Stands out for combining strong agent orchestration and reliability engineering with measurable business impact, including 60-70% cost reductions, 45% lower monthly LLM spend, and a 5x increase in developer iteration speed.”
Alexander Smith
Junior Software Engineer and Data Scientist specializing in AI/ML systems
“Built production-grade automation and ML/data pipelines at Dun & Bradstreet and ThreadNotion, spanning large-scale document classification, country risk report automation, and resilient Playwright testing for dynamic AI chat workflows. Particularly strong in turning brittle or ambiguous systems into reliable, observable, end-to-end automated platforms.”
Tara Munjuluri
Junior Software Engineer specializing in full-stack and AI systems
“Backend-focused engineer with end-to-end ownership experience on internal platforms at John Deere, including a workforce and skills system that cut manual review time by 40%. Brings a strong reliability and compliance mindset across Java/Python microservices, AWS infrastructure, and production operations, and has also built an LLM-powered RAG system over 1M+ records with emphasis on grounded outputs and observability.”
Lakshmi Tanikonda
Mid-level Software Engineer specializing in full-stack and backend systems
“Backend-leaning full-stack engineer with experience at Liberty Mutual and Airbnb, building high-scale insurance claims systems (1M+ monthly transactions) and consumer booking/pricing services (120K–180K daily requests). Strong in transactional data integrity, PostgreSQL performance tuning, and production operations (Docker/Jenkins/AWS), with measurable UX/performance wins including ~2.3s page loads and significant runtime failure reduction.”