Pre-screened and vetted.
Intern Full-Stack/AI Engineer specializing in LLM applications and cloud-native web systems
Intern Software Engineer specializing in data pipelines, security tooling, and ML for equities
Mid-level AI/Data Engineer specializing in LLMs, RAG pipelines, and cloud data platforms
Mid-Level Full-Stack Software Engineer specializing in cloud and kiosk applications
Junior Machine Learning Engineer specializing in semantic search and retrieval systems
“Built and shipped a production RAG system (“TROJAN KNOWLEDGE”) for answering questions over technical PDFs, using a 3-stage retrieval stack (BM25 + FAISS + cross-encoder) to lift F1 from 71% to 84%. Drove major performance gains with a 3-level cache (memory/Redis/disk) cutting latency from ~200ms to ~10ms, and added Prometheus/Grafana monitoring plus LangChain-based fallback logic to handle OpenAI rate limits under load.”
Junior Full-Stack Software Engineer specializing in cloud-native distributed systems
“Software engineer with JPMorgan Chase experience building a real-time operations console backend on Spring Boot/Kafka/Kubernetes and resolving peak-load latency through profiling, indexing, caching, and async processing. Also built and owned an AI-driven digital-archives metadata pipeline during a master’s at UNT using OCR + LLaMA-based prompting with validation, near-human accuracy, and human-in-the-loop guardrails.”
Executive Technology & Product Leader specializing in games, platforms, and real-time systems
“Engineering leader with gaming and fintech/trading-firm experience who built a sponsor-funded gaming rewards platform (AmEx-style) requiring integrations across Steam/Epic/Xbox/PlayStation and Discord. Emphasizes production-grade, 12-factor delivery with Terraform/Docker/CI/CD and automated testing, plus pragmatic org scaling and remote-team culture built on aligned autonomy and trust.”
Junior Software Engineer specializing in AI and cloud-native full-stack systems
“Software engineer with 2 years of professional full-stack experience plus a CS master's journey in the US, who has since focused heavily on building hackathon-winning AI systems. Stands out for combining production-minded backend architecture, TypeScript-heavy reliability work, and multi-agent LLM applications spanning physical security and insurance claims automation.”
Junior Software Engineer specializing in backend, distributed systems, and cloud platforms
“MS candidate with strong backend/data engineering focus who builds research and data systems with production-grade rigor (reproducibility, observability, restartability). Has hands-on experience securing and scaling FastAPI-based gateways in front of Java microservices, leading SQL Server→Snowflake migrations with dual-write/feature-flag rollouts, and hardening Kafka-based fleet-tracking systems against out-of-order and duplicate events.”
Mid-level Software Engineer specializing in cloud-native systems and AI automation
“Software engineer with hands-on experience shipping production AI agents and end-to-end ecommerce workflows. They built a customer support automation agent with strong guardrails and evaluation practices, then improved it post-launch using real user data to cut latency ~30% and token cost ~25%. Also drove a zero-to-one self-serve order modification product across React UI, backend services, and cross-functional alignment.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native FinTech and ERP systems
Intern Full-Stack Software Engineer specializing in AI-powered web applications
Senior GenAI Engineer specializing in LLM agents and insurance automation
Mid-level Backend Engineer specializing in distributed microservices and event-driven systems
“Software engineer (Yellow.ai) who built and productionized an AI-driven resume tailoring system using embeddings + Chroma RAG + QLoRA fine-tuning, deployed via Docker/Kubernetes with CI/CD on a CPU-only Oracle VM. Demonstrates strong reliability/evaluation rigor (custom hallucination/coverage/relevance metrics) and measurable business impact, including a 60% user satisfaction lift from improving chatbot intent accuracy with product and support teams.”
Mid-level Full-Stack & ML Engineer specializing in AI SaaS, MLOps, and cloud infrastructure
“Built and shipped an AI-powered driver ranking/assignment system at AffirmoAI using LLM intent classification + RAG over pgvector/Postgres, served via FastAPI with a React UI that explains scores. Drove measurable improvements through optimization and iteration (latency down to <800ms, adoption 60%→90%+) and implemented rigorous eval loops with dispatcher ground truth plus cold-start handling for new drivers.”
Mid-level Full-Stack Developer specializing in Angular, Java, and MERN
“Full-stack developer with 4 years of experience and an MS in Computer Science who led frontend delivery for a large airline platform (booking, check-in, and payment flows) using Angular/TypeScript with a Java backend. Emphasizes quality at scale via SonarQube monitoring, E2E/regression testing, and iterative Agile collaboration with clients using Figma.”
Mid-level Full-Stack Developer specializing in AI automation and RAG pipelines
“Frontend engineer who has led mobile-first and web React/TypeScript products end-to-end, including an expense tracking app handling sensitive financial data and a real-time messaging/activity dashboard with chat, presence, and contextual side panels. Emphasizes scalable architecture, rigorous component-boundary testing, and production-safe rollout practices (feature flags, analytics/logging, staged releases) to ship reliably in fast-paced environments.”
Mid-Level Software Engineer specializing in full-stack systems and authentication
“Full-stack engineer who led production modernization of a legacy, latency-sensitive application into a React + microservices platform, with heavy TypeScript backend work to improve reliability and maintainability. Has operated and scaled authentication/identity services in production, addressing peak-traffic latency spikes via database tuning and improved observability, and emphasizes idempotent, retry-safe workflow design.”
Entry-level ML Systems Engineer specializing in LLM infrastructure and recommender systems
“Engineer with a mature, agent-oriented approach to AI-driven software development, using structured planning, TDD, and verification loops rather than ad hoc prompting. Has hands-on experience acting as a tech lead for multiple AI agents in an LLM intelligent routing project, coordinating implementation, testing, debugging, and edge-case review with strong attention to system tradeoffs.”