Pre-screened and vetted in Texas.
Mid-Level Software Engineer specializing in backend tools and industrial automation systems
Mid-level Software Engineer specializing in cloud-native data engineering
Mid-Level Software Engineer specializing in full-stack web and backend systems
Junior Software Engineer specializing in microservices and FinTech payments
Mid-Level Software Engineer specializing in Java microservices and cloud-native development
Mid-level Backend Software Engineer specializing in Python, APIs, and data pipelines
Mid-Level Software Engineer specializing in full-stack web development and cloud
Junior Full-Stack Software Developer specializing in Java microservices and cloud CI/CD
Junior Full-Stack Python Developer specializing in cloud-native web applications
Junior Software Engineer specializing in full-stack web apps and REST APIs
Mid-Level Software Engineer specializing in IoT platforms and data pipelines
Mid-level Data Engineer / Software Engineer specializing in streaming and cloud data platforms
“Backend engineer with deep Kafka/FastAPI microservices experience who redesigned a notification pipeline to cut end-to-end latency from ~5s to ~3s (including custom partition assignment and consumer tuning). Led a high-stakes ClickUp-to-Oracle migration of 1M+ records using idempotent ETL, reconciliation, and shadow deployment to achieve >99% integrity with zero downtime, and has hands-on production security implementation with Django/DRF (JWT + RBAC).”
Mid-level AI Data Engineer specializing in GenAI, RAG, and cloud data pipelines
“LLM/agentic AI builder who deployed a production ITSM automation agent on Google ADK integrating ServiceNow and FreshService, with strong safety guardrails (human-approval gating and runbook-only command execution) and rigorous evaluation (500 synthetic tickets; 80%+ false-positive reduction). Also partnered with finance to deliver an AI agent that automated invoice/SOW retrieval and monthly reporting to account managers, reducing manual back-and-forth.”
Junior AI/Full-Stack Software Engineer specializing in ad automation and LLM systems
“Full-stack engineer with deep ad-tech/marketing automation experience, building production tools that reduce programmatic ad waste and improve search ads performance. Shipped and operated AWS-deployed, Dockerized systems with Postgres/Redis and strong observability (Datadog/OpenTelemetry), and delivered measurable impact (25k campaigns processed, 50k sites negated, 3–4 hours/week saved). Built scalable abstractions for multi-platform ad integrations, enabling rapid onboarding of additional clients.”
Mid-Level Full-Stack Software Engineer specializing in AI-enabled web platforms
“Backend/AI engineer in construction tech (HyperWater AI) who delivered major production performance wins (analytics API from ~1 hour to 0.5s) and shipped LLM features for parsing subcontractor manifests into CSI divisions with human-in-the-loop review. Also built a freelance agentic document-verification system using OCR + RAG over pgvector with robust retry/escalation logic and user feedback loops.”
Junior Software Engineer specializing in cloud-native microservices and applied AI/ML
“Built and deployed a production AI accessibility platform that turns chart and image-based graphs into real-time audio narratives for visually impaired users. Implemented a ResNet-based CV + OCR + NLP + TTS pipeline and improved performance through preprocessing, Redis caching, and Kubernetes autoscaling/rolling updates on AWS to handle traffic spikes with no downtime.”
Mid-level Full-Stack Software Engineer specializing in cloud-native apps and AI copilots
“Internship project building and deploying a LLaMA-based, RAG-enabled copilot inside a Professional Services Automation platform, enabling natural-language navigation, text-to-SQL reporting, and project/resource/budget insights across multiple modules. Addressed real production issues like context drift and vague queries with hybrid search, metadata enrichment, and an intent classification/rewriting layer, orchestrated via Apache Airflow—ultimately cutting PMO reporting time by 40%.”
“Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.”
Mid-Level Full-Stack Software Engineer specializing in cloud web apps and Microsoft Dynamics 365
Senior Full-Stack Developer specializing in Python backends, distributed systems, and AI/ML
Junior Full-Stack Software Engineer specializing in cloud-native microservices