Vetted Software Engineers

“At Trellis, built and shipped a production multi-agent, authenticated GenAI chatbot for sensitive financial account inquiries (loan/payment lookups), using dynamic model routing to control latency and cost while improving accuracy. Implemented prompt-injection defenses (Meta Prompt Guard), RAG with LangChain, and LLM-as-a-judge evaluation; the system cut manual support call volume by 40%+ and was refined through close collaboration with QA-driven user testing.”

“Frontend web developer who owned end-to-end delivery for multiple client websites at Vox Interactif and RGI Solutions, including solo launches and rigorous cross-device/browser QA. Experienced with Joomla/WordPress ecosystems (selecting and customizing reliable add-ons) and structured rollout practices (staging/sub-branch + client sign-off). Currently upskilling in React by building a custom wiki-style dashboard for fantasy novel worldbuilding.”

“Founding engineer at a startup building LLM/agentic workflows for public-safety customers, with hands-on experience delivering a hybrid on-prem + secure cloud solution to meet strict compliance needs. Implemented OpenTelemetry observability for multimodal agentic systems behind closed networks and used the resulting traces to optimize prompting/token usage for customer-specific security integrations. Regularly runs technical workshops and supports pre/post-sales by translating integration feedback into product roadmap decisions.”

“Built and deployed an LLM-to-SQL automation system in a closed/internal environment, using a retriever–reranker–validator architecture on Kubernetes with strong security controls (semantic + rule-based validation and RBAC), achieving 99% uptime and cutting manual query time ~40%. Also worked on genomic sequence classification and semantic search workflows, orchestrating data prep with Airflow, tracking/deploying with MLflow, and optimizing distributed multi-GPU training on a university Kubernetes cluster.”

“Built and productionized a RAG-based semantic search system for video-derived data, focusing on measurable success metrics (p95 latency, reliability, cost/request) and strong observability (prompt versions, retrieved docs, tool calls, token usage). Experienced in diagnosing real-time issues in LLM/agentic workflows and in supporting go-to-market efforts through tailored technical demos, rapid POCs, and post-close onboarding.”

“Backend/data engineer who built a production analytics data service (Python/FastAPI on AWS/Postgres with PySpark ETL) handling millions of records per day and drove major latency improvements (10–15s to <2s) via indexing, Redis caching, and shifting aggregations into ETL. Also shipped an LLM-based natural-language-to-SQL assistant end-to-end with strong guardrails (schema restrictions, read-only validation, RBAC, masking) and designed a multi-step agent workflow with verification and fallback logic.”

“Backend engineer with fintech/transaction-processing experience who built and optimized a Spring Boot + PostgreSQL + AWS service handling money transactions, resolving peak-traffic latency via query/index and connection pool tuning. Shipped an LLM-driven risk-flagging workflow integrated via a FastAPI Python service, owning prompt design, validation guardrails, monitoring, and human-in-the-loop escalation to reduce false positives and improve precision over time.”

“Software engineer and co-founder with 0-to-1 SaaS experience who built and owned an end-to-end reporting/analytics dashboard on Next.js App Router + TypeScript, including Postgres schema design, aggregation query optimization, and post-launch performance/monitoring. Has delivered measurable React dashboard performance gains (~35% improvement in time-to-insight) and built durable, idempotent job/state-machine workflows using serverless functions and Postgres.”

“Backend engineer with production experience at KeyBank building high-volume Java/Spring Boot services on Azure with PostgreSQL/Oracle, including async job ingestion and tracking. Demonstrates strong reliability/performance debugging (HikariCP pool exhaustion, DB contention) and has shipped an LLM-powered data analysis/summarization feature with robust production guardrails (validation, shadow testing, deterministic fallbacks, audit logs).”

“Backend/infra-focused engineer who owned production systems for distributed ML experimentation (hyperparameter tuning across a cluster with GPU scaling, custom scheduling, and checkpoint-based fault tolerance). Also built and operated a low-latency log validation service using queued async workflows with idempotency, retries/backoff, and strong observability, plus experience building resilient Selenium-based browser automations for complex multi-step web flows.”

“Built and owned a production RAG search/Q&A platform at Data Integrity First for a client with a large, hard-to-search document library, deployed on AWS. Drove major adoption gains by adding source attribution (users trusted answers more) and improved system performance with guardrails, logging, and iterative chunking/OCR normalization—cutting fallback rate from ~22% to under 10%.”

“Startup-experienced builder exploring an ambitious “internet 2.0” concept: a decentralized wireless mesh network using custom hardware nodes, with a security-first communications goal. Has thought through adoption mechanics via at-cost node distribution, usage-based crypto incentives, and an AR area-control game to drive network growth; also brings practical insight into what VCs value from working at startups including one owned by a PE firm.”

“India-based engineering leader/player-coach managing ~20 people and three products, while still shipping hands-on in Python/Golang across 8–10 microservices deployed on GCP (Kubernetes) and AWS (ECS). Has led end-to-end delivery (design through QA) and owned production reliability improvements (including building a Slack alerting bot). Strong domain exposure in utilities (MDM/meter readings, billing/rate calculations) and financial integrations (GL code tagging), plus side projects in Golang around LLM API cost-optimization.”

“AI/LLM engineer with crypto/social-data domain experience who built an end-to-end AI trading signals and analysis backend using Next.js, Inngest, Gemini, and Supabase, including real-time progress UX and robust rate-limit/reliability handling. Also published an MCP SDK on NPM for authenticated agent tool access and built autonomous Twitter-based AI agents; strengthened reliability at LunarCrush by adding CI-gated E2E testing across web and mobile (Cypress/Maestro).”

“Built and showcased a self-made "Scholar AI" education web app that answers student queries and uses a RAG pipeline to ingest PDFs and generate MCQs for exam prep. Also delivered an AI solution for generating ad creatives and ad copy from keywords, emphasizing clear communication with non-technical stakeholders.”