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Vetted Prompt Engineering Professionals
Pre-screened and vetted.
Senior Full-Stack & AI/ML Engineer specializing in cloud-native platforms and LLM systems
Mid-level AI Engineer specializing in LLM agents, RAG, and enterprise GenAI
Intern Data Scientist specializing in NLP and Large Language Models
Mid-level AI/ML Data Engineer specializing in analytics, ML pipelines, and LLM applications
Mid-Level Software Engineer specializing in cloud-native distributed systems
Junior AI Product Engineer specializing in LLM workflows and analytics automation
Mid-level AI/ML Engineer and Developer Educator specializing in GenAI, RAG, and AI community building
Senior Management Consultant specializing in financial services capital markets
Intern Software Engineer specializing in systems programming and game development
Senior Applications Engineer specializing in ERP Financial Systems and GenAI automation
Mid-level AI Engineer specializing in LLM orchestration and production AI systems
Mid-level Software Engineer specializing in backend microservices and cloud-native systems
Senior Technical Artist specializing in XR, game engines, and generative/agentic AI
Sean Keppler
Principal Space Systems Engineer specializing in spacecraft and payload architecture
“Previously supported capital raising at Space Ocean Corp by securing several thousand dollars in grant funding and building investor-readiness/outreach materials. Has early exposure to VC/studio/accelerator meetings and articulates nuanced differences in their incentives and time horizons. Interested in refining skills as an early-stage CTO and is highly committed to entrepreneurship.”
Abhishikth Meesala
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection
“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”
Varaprasad Bathula
Intern AI/ML Engineer specializing in LLM applications and data infrastructure
“Hands-on LLM practitioner who built a production document-processing pipeline in Python, tackling long-document handling and latency with chunking/batching and a user-driven correction feedback loop. Experienced operationalizing AI workflows with Kubernetes (CronJobs, autoscaling, scheduled data cleaning and weekly retraining) and applying structured testing/evaluation (E2E, LLM-as-judge, HITL) while communicating solutions clearly to non-technical clients using visual diagrams.”
Ajith P
Mid-level Backend Software Engineer specializing in AI workflow automation for finance and healthcare
“Backend/AI engineer with healthcare domain experience who built a patient journey analytics API (FastAPI/PostgreSQL/Snowflake/Redis) and debugged peak-hour latency down from ~900ms to ~50ms via indexing and query optimization. Shipped an LLM-powered clinical summary/recommendation assistant end-to-end and designed a multi-step risk evaluation agent workflow with safety guardrails against hallucinations and unsafe outputs.”
Harinee Mohanakrishnan
Junior AI/ML & Cloud Software Engineer specializing in LLM applications
“AI engineer (2+ years; pursuing an online MS at UIUC) who has shipped an AI-powered voice screening platform end-to-end on GCP with strong production monitoring and measurable hiring-process impact (80% reduction in unqualified pass-through; ~50+ hours saved per role). Also built and deployed an AWS-based context-aware hybrid search system using OpenSearch as a vector store, and has hands-on experience with multi-agent LLM orchestration (ReAct) and structured-output guardrails.”