Pre-screened and vetted.
Mid-level Full-Stack & Integration Engineer specializing in Insurance APIs
“Hands-on engineer focused on taking complex/LLM-style workflows from prototype to production, emphasizing robust error handling, CI/CD + Docker deployment, and deep observability (Kibana/Rancher/Grafana). Experienced customizing client integrations and data transformations (XML/JSON/PDF to SFTP) and debugging agent workflows with traces, prompt verification, and human-in-the-loop safety controls. Partnered with product/ops to drive adoption, including a MuleSoft migration that improved partner onboarding speed by ~50%.”
Intern Software Engineer specializing in cloud, full-stack, and AI systems
“Built a production LLM-assisted workflow for customer configuration data migrations, combining agentic parsing with deterministic validation and fail-safe pipeline design. Stands out for turning messy ERP and operational data into reliable, repeatable transformations while improving accuracy and cutting manual effort by more than 80%.”
Mid-level Software Engineer specializing in AI/ML for FinTech and Healthcare
“Built and deployed an end-to-end fintech product, FinSight, for bank statement analysis and financial Q&A using a production-style RAG architecture. Stands out for combining FastAPI, OpenAI embeddings, FAISS, hybrid SQL/vector retrieval, and practical reliability work like chunking optimization, validation, and low-latency performance tuning.”
Mid-level Software Engineer specializing in AI pipelines and enterprise integrations
“Candidate has 4 years of experience and appears strongest in customer-facing implementation and AI-enabled workflow automation. They describe owning deployments end-to-end, putting an LLM support assistant with RAG and function calling into production, and improving support operations with a 30% reduction in resolution time and 25% gain in agent productivity.”
Mid-level Software Engineer specializing in full-stack and ETL systems
“Backend engineer with end-to-end ownership experience across enterprise SaaS and high-volume data systems, including PostgreSQL/.NET services at Visual Lease and ETL pipelines at Broadridge processing millions of records for Fortune 500 clients. Stands out for combining production support, observability thinking, and pragmatic architecture tradeoffs, while also experimenting with LLM-powered job application automation using Claude.”
Mid-level Full-Stack Software Engineer specializing in cloud-native and Generative AI systems
“Frontend-leaning full-stack product engineer with experience in insurance and financial analytics, combining UI design, React/TypeScript implementation, and backend integration. Stands out for shipping data-heavy dashboards, real-time collaborative features, and early generative AI document-analysis workflows using Spring Boot, LangChain, and AWS Bedrock.”
Mid-level Full-Stack Developer specializing in frontend web applications
“Backend-focused engineer with banking-domain deployment experience who has owned releases end-to-end, from discovery and API/database implementation through post-launch stabilization. Brings a reliability-first mindset across distributed systems, incident response, and messy real-world data handling, and has also applied that foundation to retrieval-based LLM workflows in production-oriented cloud environments.”
Junior Software Engineer specializing in Full-Stack and GenAI/LLM applications
“LLM/RAG practitioner building clinician-facing AI search and Q&A inside EHR workflows, focused on trust, latency, and safety (grounded answers with citations, PHI controls, encryption/audit logs). Demonstrated real-time incident response for production LLM systems (e.g., fixing a metadata-filter deployment regression to prevent irrelevant results/cross-patient leakage) and strong demo/enablement skills for mixed technical and clinical stakeholders; also shipped a multi-model RAG tool at OrbeX Labs with upload/search/audit features for day-to-day adoption.”
Mid-level AI/ML Engineer specializing in MLOps and cloud-deployed ML systems
“ML/AI engineer who built and productionized an NLP system at PurevisitX, orchestrating end-to-end ML workflows with Airflow (S3 ingestion through auto-retraining) and optimizing for drift and low-latency inference. Also partnered with Citibank risk teams on a fraud detection model, translating results via dashboards and iterating thresholds based on stakeholder feedback.”
Mid-level GenAI/ML Engineer specializing in LLM systems and RAG chatbots
“Built and shipped a production agentic LLM analytics platform that lets non-SQL business users query relational databases in plain English via a RAG + LangChain/LangGraph workflow and FastAPI service. Emphasizes safety and reliability with guardrails (validation/access control), testing/evaluation frameworks, and performance optimization (caching, monitoring, Dockerized scalable deployment), reducing dependency on data teams and speeding analytics turnaround.”
Mid-level Machine Learning Engineer specializing in IoT, edge AI, and enterprise ML
“Built and productionized an LLM/RAG question-answering service over technical documentation, focusing on retrieval quality (reranking + IR metrics), latency, and scaling. Experienced orchestrating end-to-end ETL/ML workflows with Airflow/Prefect/AWS Step Functions and improving reliability via parallelism, retries, and shadow testing. Also delivered an explainable healthcare risk-flagging classifier with a stakeholder-friendly dashboard for a non-technical program manager.”
Senior Software Engineer specializing in full-stack platforms and real-time analytics
“Full-stack engineer with a strong builder mentality who has designed greenfield cloud-native ingestion platforms, customer-facing CAD/configuration tools for manufacturing automation, and self-service forecasting products. Particularly compelling is their ability to translate ambiguous workflows into robust systems spanning React, Node.js, shared TypeScript/Zod schemas, cloud queues, and even proprietary hardware runtimes.”
Mid-level Software Engineer specializing in backend microservices and Healthcare IT
“Backend and distributed-systems engineer with experience integrating LLM capabilities into clinical data workflows at CVS. Stands out for treating AI as an engineering accelerator rather than a shortcut, with strong emphasis on validation, observability, Kafka-based async pipelines, and safe multi-agent orchestration for production systems.”
Mid-level Full-Stack Java Developer specializing in microservices and cloud-native systems
“Senior full-stack engineer with strong healthcare domain experience who has shipped an Azure OpenAI RAG-based patient medication support chatbot to production, driving ~10K queries/month and a reported 38% reduction in call center volume. Also builds polished real-time React/TypeScript pharmacy tooling and operates large-scale Python/Spark ETL pipelines (~12M records/day) with strong API design, observability, and cloud deployment experience across Azure/Kubernetes and AWS.”
Mid-Level Forward Deployed AI Engineer specializing in RAG systems and backend microservices
“LLM solutions practitioner with SOC/alert-triage experience who takes LLM prototypes to production using RAG (Pinecone), FastAPI services, guardrails, CI/CD, monitoring, and robust fallback logic. Known for rapid real-time debugging of embedding/vector and agent workflow issues, and for driving adoption through code-first workshops and sales-aligned custom demos with measurable improvements (35% faster triage; 40% increase in correct tool usage).”
Mid-level Machine Learning Engineer specializing in data security and GenAI systems
“Built Hexagon’s production Text-to-CAD Copilot that converts text and rough sketches into editable CAD code, combining GraphRAG (Neo4j/LangChain) with a Gemini-powered vision module and multi-agent geometric validation—cutting manual modeling from a day to ~45 seconds and driving retrieval latency below 50ms. Also has large-scale GCP data/ML orchestration experience (Airflow/Cloud Composer, Dataflow, Pub/Sub, Snowflake) processing 50M+ daily records with drift monitoring and automated reliability controls.”
Mid-level Data Scientist/Data Analyst specializing in ML, BI dashboards, and ETL pipelines
“Data/ML practitioner with experience at Humana and Hexaware, focused on turning messy, semi-structured datasets into production-ready pipelines. Built an age-prediction model from book ratings using heavy feature engineering and multiple regression models, and has hands-on entity resolution (deterministic + fuzzy matching) plus embeddings/vector DB approaches for linking and search relevance.”
Mid-level Data Engineer specializing in cloud data pipelines and machine learning
“Experience spans college-built AWS-hosted Python/Flask web apps and enterprise data work at General Motors, including PostgreSQL query optimization on millions of records and multi-tenant-style data isolation using group-based, column-level permission grants. Also built an AWS-hosted meat price prediction dashboard using Dash/Plotly and ran large nightly data pipelines orchestrated with Apache Airflow.”
Mid-Level Data/ML Engineer specializing in Generative AI and cloud data platforms
“Built and productionized an LLM-based financial document analysis system using a RAG pipeline, including robust ingestion/chunking/embedding workflows, vector DB retrieval, and an AWS-deployed FastAPI service containerized with Docker. Demonstrates strong applied expertise in improving retrieval quality and latency at scale, plus hands-on experience debugging agentic/LLM workflows with monitoring and trace-based analysis while supporting demos and customer-facing adoption.”
Junior Business & Data Analyst specializing in FinTech and banking analytics
“Analytics professional with Travelex experience spanning SQL ETL, Python-based machine learning workflows, and Power BI dashboarding in risk, fraud, and AML contexts. Stands out for replacing a $150K+ third-party compliance tool with internal dashboards and for materially improving operational efficiency through alert tuning, cutting alert volume by 50% and false positives by 60%.”
Mid-level Business Analyst specializing in healthcare data and application consulting
“Analytics professional with University of Florida experience in occupational health reporting, including bloodborne pathogen and needlestick exposure programs. Stands out for turning messy healthcare operational data into trusted, analysis-ready reporting assets using SQL and Python, while partnering closely with stakeholders to define reliable metrics and improve operational oversight.”
Junior Java Full-Stack Developer specializing in Spring Boot and REST APIs
“Backend/data engineer with hands-on experience building end-to-end data pipelines and Spring Boot services, including systems processing up to 1 million records per day. Demonstrates practical strength in reliability engineering, API versioning, external data ingestion, and early-stage delivery with CI/CD, observability, and pragmatic architecture choices.”
Mid-level Full-Stack Engineer specializing in Java microservices for FinTech
“Fullstack engineer with strong backend depth who has owned complex digital banking modernization work end-to-end, spanning React UI workflows, Spring Boot microservices, API design, and event-driven integrations. Stands out for balancing technical architecture with user clarity, especially in ambiguous environments where stakeholder feedback reshaped workflows after launch.”
Senior Full-Stack Developer specializing in cloud-native web platforms
“Enterprise front-end engineer with strong Angular ownership across high-stakes products in healthcare, finance, and manufacturing, including a hospital kiosk app, Bank of America portfolio reporting, and a CMS-driven marketing site that has run smoothly for 5 years with no IT support. Stands out for combining UI architecture, measurable performance gains, and production-safe delivery strategies like AWS-based canary releases.”