Pre-screened and vetted.
Senior Customer Success & Implementation Leader specializing in regulated SaaS onboarding
“Application security and customer-facing delivery professional with deep experience in eCourt/public portal modernization, protecting sealed records and PII under statutory constraints. Has led threat modeling, phased remediation/risk acceptance to hit legislatively mandated launch dates, and implemented SAST/DAST/SCA programs in CI/CD on AWS/EKS with strong observability-driven troubleshooting and stakeholder alignment.”
Mid-level Software Engineer specializing in backend engineering and applied AI workflows
“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.”
Mid-level Site Reliability Engineer specializing in cloud infrastructure and Kubernetes
“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.”
Mid-level Software Engineer specializing in AI, full-stack development, and RAG systems
“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%.”
Junior Mechanical Engineer specializing in energy storage and fuel cell systems
“Mechanical/manufacturing professional (not a software/Next.js candidate) who emphasizes applying Lean/Six Sigma-style manufacturing quality and continuous improvement tools (Kaizen, PFMEA/DFMEA, DOE, DMAIC, root cause analysis). Target base salary stated as 130,000.”
Junior Machine Learning Engineer specializing in predictive modeling and GenAI RAG systems
“LLM engineer who built and deployed an emotionally intelligent AAC communication system using an emotion-aware RAG pipeline (Empathetic Dialogues + GoEmotions) and a PEFT-adapted model. Experienced with LangChain/LangGraph and custom Python orchestration, focusing on reliability (guards, schema validation, fallbacks), latency optimization, and rigorous evaluation (automatic metrics + human-in-the-loop), with a reported 18% user satisfaction improvement.”
Junior Full-Stack Developer specializing in React/Next.js, Node.js, and AWS
“Led an end-to-end build of bhangrascape.ca, making key architecture choices across Next.js/Node/Postgres on AWS and implementing S3-based media storage with presigned URLs. Strong focus on quality and reliability via Zod validation, Jest tests, Postman endpoint testing, and CI/CD with GitHub Actions, plus hands-on UX ownership from Figma prototyping through reusable React components and A/B testing.”
Mid-level AI/ML Engineer specializing in production ML, MLOps, and NLP
“Built and deployed a transformer-based clinical document classification system that processes unstructured clinical notes in a HIPAA-compliant healthcare setting, served via FastAPI on AWS and integrated into an Airflow/S3 pipeline. Demonstrates strong end-to-end MLOps skills (data quality remediation, low-latency inference optimization, monitoring with MLflow/CloudWatch) and effective collaboration with clinicians to drive adoption.”
Executive Finance Leader specializing in FP&A, BI, and cash flow optimization
“Founder and financial-operations-focused consultant who builds FP&A/BI frameworks for early-stage and legacy businesses, including KPI systems tied to month-end close and integrated manufacturing/distribution datasets (BOM, PPV, rolling forecasts). Drove a 400% cash-position increase for a distribution client by redesigning collections analytics (customer-level DSO + proprietary PTC ratio) and has coached PE-installed executives through U.S. operational/legal and cultural nuances.”
Junior Machine Learning Engineer specializing in multimodal systems and LLMs
“Built and productionized a domain-specific LLM-powered RAG knowledge assistant at JerseyStem for answering questions over large internal document corpora, owning the full stack from FAISS retrieval and LoRA/QLoRA fine-tuning to AWS autoscaling GPU deployment. Drove measurable gains (28% accuracy lift, 25% latency reduction) and improved reliability through hybrid retrieval, grounded decoding, preference-model reranking, and Airflow-orchestrated pipelines (35% faster runtime), while partnering closely with non-technical stakeholders to define success metrics and ensure adoption.”
Mid-level Backend Engineer specializing in distributed systems and industrial IoT
“Backend/Python engineer focused on real-time sensor/IoT analytics: built dashboards and a high-throughput ingestion pipeline (MQTT -> Python worker -> TimescaleDB) with buffering, batch inserts, and validation. Strong Kubernetes + GitOps practitioner (Dockerized microservices, HPA, probes, ArgoCD) who has handled production incidents like CrashLoopBackOff under peak load and supported an on-prem analytics migration to AWS using shadow traffic and rollback plans.”
Entry AI Engineer specializing in LLM agents, RAG, and computer vision
“Robotics/AV-focused candidate who contributed to an F1TENTH autonomous vehicle college project, building key autonomy components from raw sensor data to driving commands. Strong in perception and state estimation (visual odometry, particle-filter localization), plus mapping (occupancy grids) and planning/control (RRT, Gap Follow, PID), with hands-on ROS tooling and simulation validation in Gazebo/RViz and ROS environment containerization using Docker.”
Senior Automation QA Engineer specializing in web, API, and enterprise platforms
“QA professional with end-to-end ownership who combines automated, rule-based data validation (expected vs actual) with structured CAPA practices (5 Whys, Pareto, SOP updates, in-line checks, and hands-on training). Experienced coordinating multi-workstream QA timelines via centralized dashboards, weekly cadence, and escalations with third-party/global stakeholders.”
Junior Machine Learning Engineer specializing in LLM fine-tuning and semantic retrieval
“Backend engineer with legal-tech and AI workflow experience: built JurisAI, an end-to-end legal research system using OCR + embeddings + Pinecone vector search to deliver citation-grounded LLM answers with safe failure modes (~90% recall@K). Also led a GW Law metadata migration into Caspio with batch validation and parallel rollout, and has strong FastAPI/GCP production reliability and observability practices.”
Mid-level AI Engineer & Researcher specializing in healthcare AI and multimodal LLM systems
“Backend/ML engineer focused on clinical AI transparency who built ShifaMind, an explainability-enforced clinical ML system using UMLS/MIMIC-IV/PubMed data with RAG, GraphSAGE, and cross-attention. Demonstrated strong production engineering via FastAPI API design and safe migrations (feature flags/shadow inference), plus HIPAA-aligned auth/RLS patterns; also delivered a real-time comet detection system reaching 97.7% accuracy.”
Mid-level Software Developer specializing in indie game development and full-stack apps
“Robotics software engineer who built the perception-to-planning pipeline for an autonomous bipedal robot: synchronized and fused 3D LiDAR + multiple depth cameras in ROS1 (tf2/message_filters) to produce combined point clouds and 2.5D maps, then implemented and benchmarked A*/D*/RRT plus hybrid A* footstep planning in simulation. Also founded a software company and personally owned CI/CD, security checks (CodeQL), and release automation (custom release bot + Slack notifications).”
Mid-Level Software Engineer specializing in full-stack development and data engineering
“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).”
Mid-Level Full-Stack Product Engineer specializing in TypeScript and React
“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.”
Mid-Level Software Engineer specializing in distributed systems and cloud microservices
“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.”
Director-level Software Development Leader specializing in FinTech, Blockchain, and AI
“Bootstrapped founder with a technical background who has already built an MVP SaaS loyalty and referral platform plus a tablet/mobile POS companion product, leveraging Azure and Google Cloud support rather than outside capital. Focused on learning-by-building, resource-efficient execution, and forming highly motivated, equity-aligned teams.”
Senior Marketing Leader specializing in full-funnel growth, lifecycle and product marketing
“B2B growth and partnerships operator with experience at Convera leading GTM for a cross-border payments offering and driving a ~17% lift in qualified leads through refined positioning and multi-channel activation. Has run data-driven funnel experiments (Dentacloud) and built association-based co-marketing partnerships measured through both top-of-funnel engagement and downstream pipeline influence.”
Mid-Level Software Engineer specializing in LLM applications, RAG, and OCR automation
“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.”
Mid-level GenAI Engineer specializing in LLM automation, RAG, and document intelligence
“Built and deployed a production GenAI resume screening and matching system for Florida Atlantic University, focused on improving recruiter efficiency and search relevance. Demonstrates strong RAG engineering (embeddings, query rewriting, metadata filtering, threshold tuning) plus practical reliability work (grounding constraints, fallbacks, and evaluation using real user queries) using Python REST APIs and orchestration frameworks like LangChain and LlamaIndex.”
Mid-level Software/Data Engineer specializing in cloud ETL pipelines and data infrastructure
“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.”