Pre-screened and vetted.
Intern Machine Learning & Full-Stack Engineer specializing in computer vision and healthcare AI
“AI/ML-focused backend engineer who shipped two production systems: PersonaPal (agentic LLM chatbot with RAG, FAISS-based retrieval, and Redis semantic caching) and CervixScan (clinical diagnostics platform with PostgreSQL data modeling and human-in-the-loop safety for low-confidence predictions). Demonstrates strong performance/reliability work (indexed vector search, caching, query optimization to ~200ms) and end-to-end ownership from orchestration design through deployment.”
Mid-Level Full-Stack Software Engineer specializing in hybrid cloud platforms
“Full-stack engineer from HPE GreenLake who built and owned a cloud/hypervisor resource management experience end-to-end, including Postgres modeling, typed REST/GraphQL integrations, and resilient provisioning workflows. Drove a centralized Redux-based UI architecture that boosted dev velocity by 50% across 30+ teams, and continued post-launch ownership with DR integrations (AWS/GCP/Azure) plus expanded Cypress testing and observability.”
Mid-level Software Engineer specializing in data pipelines and backend APIs
“Data engineer with Webster Bank experience owning end-to-end pipelines (APIs + databases) processing millions of records/day, improving data quality (25–30% fewer issues) and reliability (~99.9% successful runs). Built resilient external data ingestion/scraping systems (schema-change validation, idempotent backfills, monitoring/alerts) and shipped a FastAPI service exposing curated datasets with versioning and consistently low latency.”
Intern Full-Stack Software Engineer specializing in AI/ML and cloud
“Built a Python-based geospatial machine learning backend for PFAS contamination risk mapping, including reproducible feature pipelines, ensemble modeling, and a FastAPI layer for visualization/analysis. Emphasizes data integrity and robustness (CRS/coverage checks, fail-fast validation) and has led safe backend refactors using feature flags, idempotent backfills, and Postgres RLS for secure, queryable results delivery.”
Senior Full-Stack Java Developer specializing in capital markets and trading systems
“Backend/data engineer with production experience in payment initiation/processing services built in Python/FastAPI, emphasizing reliability patterns (JWT/RBAC, timeouts, retries, circuit breakers). Has delivered AWS deployments on ECS (ALB, autoscaling, CI/CD to ECR) plus Lambda-based reporting, and built AWS Glue ETL pipelines with schema evolution and CloudWatch monitoring. Also modernized a legacy SAS reporting platform to Python/PostgreSQL with regression parity testing and parallel-run migration, and achieved a 70% SQL performance improvement.”
Staff Full-Stack Software Engineer / Tech Lead specializing in scalable web platforms
“Frontend engineer who has led end-to-end delivery of a bag tag management application and contributed to a bank wealth application using micro-frontends. Emphasizes scalable architecture, reusable component systems (Storybook), performance techniques (lazy loading/code splitting), and quality/security tooling (Veracode, Wiz Scan, SonarQube) with a disciplined multi-environment release process.”
Junior Software Engineer specializing in machine learning and data science
“Python backend engineer who built a personal LLM-powered AI code review tool that parses code into context-preserving diff chunks and uses the OpenAI API to analyze and summarize changes. Has hands-on Kubernetes deployment experience (replicas, rolling updates, ConfigMaps/Secrets, health probes) and follows GitOps-style, declarative CI/CD workflows; also has experience designing streaming/event-style processing with attention to reliability and observability.”
Junior Software Engineer specializing in cloud-native DevOps and GenAI
“Cloud-focused engineer with hands-on experience deploying production cloud-native REST APIs on AWS using Pulumi IaC, containerization, and CI/CD, with strong emphasis on secure credential management and operational monitoring via CloudWatch. Also has IoT troubleshooting experience across edge hardware constraints and networking (TLS handshake failures), plus Python-based configurable data-processing tools and customer-facing requirements translation.”
“Backend-focused intern who built and refactored the backend for an LLM-driven gifting mobile app using FastAPI, tackling high-latency LLM + product-API workflows. Implemented async worker-pool/queue processing with Redis caching plus retries/fallbacks, cutting end-to-end suggestion latency from ~4–5 seconds to ~1 second while improving reliability and rollout safety via staged migrations and testing.”
Senior AI/ML Engineer specializing in production-grade LLM systems for regulated finance
“AI/LLM engineer with published work who built FinVet, a production financial misinformation detection system using multi-pipeline RAG, confidence-based voting, and evidence-backed outputs (F1 0.85, +37% vs baseline). Also built NexusForest-MCP, a Dockerized Model Context Protocol server exposing structured global deforestation/carbon data via SQL tools for reliable LLM tool use. Previously delivered borrower risk-rating (PD) models at BMO Financial Group that were validated and integrated into an enterprise credit system through close collaboration with credit officers and portfolio managers.”
Mid-level Full-Stack .NET Developer specializing in cloud-native microservices
“Full-stack .NET engineer with cloud and applied GenAI experience who shipped a real-time policy status tracking module at Lincoln Financial using ASP.NET Core/.NET 8, Kafka, Angular, SQL Server, Redis, and AKS autoscaling. Also delivered a production internal LLM+RAG support assistant at Honeywell with strong security/guardrails (PII masking, RBAC) and a rigorous eval/regression loop built on a 200-question gold set.”
Senior Data Engineer specializing in data infrastructure and marketing/CRM analytics
“Salesforce-focused implementation/solutions engineer from Full Circle Insights who owned end-to-end campaign attribution and reporting deployments for multiple customers at once (3–5 concurrently), including sandbox testing, KPI monitoring, and rollback-safe migrations from legacy reporting. Also builds personal multi-agent workflows and uses Claude Code to rapidly scaffold data/analytics scripts like an advertising optimization parser over CSV/XLSX inputs.”
Mid-level AI Engineer specializing in LLMs, RAG, and healthcare AI
“Built and scaled an AI-powered voice/chat patient engagement platform at Penn Medicine from early prototype into production clinical workflows, focusing on latency, edge cases, and user trust. Strong in LLM reliability engineering (structured prompts, validation/fallbacks), real-time troubleshooting with observability, and cross-functional enablement through pilots, demos, and sales/customer partnership.”
Mid-Level Software Engineer specializing in cloud-native microservices and analytics platforms
“JavaScript engineer with a track record of diagnosing and fixing real performance issues end-to-end—profiled a charting library freeze on large datasets, rewrote layout logic to batch updates, added tests, and got the PR merged upstream. Also has experience stabilizing backend services in ambiguous, fast-moving projects by defining priorities, tightening API contracts, and owning delivery through deployment.”
Mid-level Full-Stack Java Developer specializing in Angular and Spring Boot microservices
“Full stack Java developer (5 years Java/Spring Boot) building a mortgage-focused rule engine platform used by business users and developers. Experienced scaling data-intensive microservices on AWS (RDS/S3/SQS) and optimizing high-volume rule processing with SQL tuning, caching (KIE container), and asynchronous task decoupling; also delivers modern UIs in Angular and React (Redux/Toolkit).”
Mid-level Data Analyst/Data Engineer specializing in BI, ETL pipelines, and cloud analytics
“Data engineer focused on marketing/web analytics and external API pipelines, handling ~10M records/week. Built Azure-based ingestion and PySpark transformations with rigorous data quality checks, then served curated datasets into Synapse/Redshift for Power BI. Also designed an Airflow-orchestrated crypto REST API pipeline with monitoring, retries/exponential backoff, schema-change detection, and backfill-friendly reprocessing.”
“Analytics-focused candidate with internship and project experience at Recotap and CoUnderscore, combining SQL, Python, and BI dashboards to turn messy marketing and engagement data into decision-ready reporting. Stands out for tying analytics work to business outcomes, including ~15% CTR improvement, identifying ~40% misattributed spend, and enabling a ~$75K budget shift through better targeting.”
Entry Product Builder specializing in AI-assisted software prototyping
“Early-stage product engineer who has shipped an AI-assisted workflow web app end-to-end, spanning Next.js/TypeScript frontend, Python-backed LLM APIs, Postgres analytics, and async backend workflows. Strong ownership after launch as well, including usage tracking, prompt and UX iteration, latency reduction, and measurable database performance improvements.”
Senior IT Business Systems Analyst specializing in UAT, project delivery, and regulated platforms
“Worked on a P&C insurance integration project at Accenture, using SQL to unify policy, billing, and claims data from APIs and ETL pipelines into clean reporting tables. Demonstrated hands-on experience with data quality validation, window-function-based transformations, and query performance tuning, helping business teams get a single reliable view for faster claims processing and management reporting.”
Junior software developer specializing in data analytics and machine learning
“Entry-level software engineer who independently built an AI-powered feedback aggregation and analytics dashboard end-to-end using Cloudflare Workers, D1, and React. Stands out for combining serverless backend design, LLM-based categorization, and thoughtful UI/UX polish, with a practical approach to production debugging and data reliability.”
Mid-level AI/ML Engineer specializing in GenAI, NLP, and financial systems
“GenAI/ML engineer with hands-on experience building production financial intelligence and document summarization systems at Citibank. Stands out for combining LLM fine-tuning, hybrid RAG, multi-agent workflows, and strong MLOps/observability practices to deliver measurable business impact, including 60% faster analyst retrieval, 31% higher precision, and 99%+ uptime.”
Mid-level AI & Machine Learning Engineer specializing in FinTech
“ML/AI engineer with hands-on experience building production systems in financial services, including a real-time underwriting analytics platform at Hartford Financial Services. Stands out for combining classic ML, low-latency API deployment, monitoring, and emerging LLM/RAG design patterns, with measurable impact including 20% better decision accuracy, sub-200ms latency, and 5M+ records processed daily.”