Pre-screened and vetted.
Mid-level AI Engineer specializing in LLMs, RAG, and data engineering
“AI Engineer Co-Op at Northeastern University who built a production Patient Persona Chat Bot to help nursing students practice clinical interactions, fine-tuning Llama 3 and integrating a LangChain + Pinecone RAG pipeline deployed on Amazon Bedrock. Emphasizes clinical accuracy and reliability with guardrails, retrieval filtering, and continuous evaluation, and also brings strong data engineering/orchestration experience (Airflow, EMR/PySpark, ADF, dbt, Databricks, Snowflake).”
Mid-level AI Engineer & Data Scientist specializing in LLMs, RAG, and multimodal systems
“LLM/GenAI engineer who built a production AI-powered credit risk policy summarization and compliance alerting platform at HCL Tech, focused on factual accuracy and auditability for a financial client. Implemented a multi-retriever LangChain RAG architecture with citations-only prompting, fallback agents, and human-in-the-loop legal review—cutting manual review time by 35% and scaling to 12 teams.”
Mid-level Full-Stack Developer specializing in Java, Spring Boot, and cloud-native web apps
“Full-stack engineer with strong React/TypeScript and Java Spring Boot microservices experience who has built end-to-end task management and real-time, data-intensive dashboards. Demonstrates practical depth in security (JWT, RBAC, token refresh), performance optimization (indexing/aggregations, virtualization, caching), and cloud deployment (AWS, Docker, Jenkins, Kubernetes).”
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered solutions
“AI/NLP-focused practitioner who built a zero-/few-shot LLM event extraction system on the long-tail Maven dataset, combining prompt-structured outputs with LoRA/QLoRA fine-tuning and rigorous F1 evaluation. Also implemented entity resolution/data cleaning pipelines and embedding-based semantic search using Sentence-BERT + FAISS, and has healthcare experience delivering a multilingual speech/translation mobile prototype using HIPAA-compliant Azure Cognitive Services.”
Mid-level Applied AI Engineer specializing in agentic LLM workflows
“AI engineer with production experience building a LangGraph-based, stateful multi-agent system at MetLife to automate complex insurance claims adjudication, integrating document discovery, Azure Document Intelligence OCR/extraction, and health data analysis. Strong in agent orchestration and production deployment (Docker + FastAPI REST APIs), with a structured approach to reliability, evaluation, and stakeholder-driven requirements.”
Junior Software Engineer and ML Researcher specializing in full-stack and applied deep learning
“LLM engineer who built a production-style educational questionnaire generation system (MCQs/fill-in-the-blanks/short answers) using Hugging Face models (BERT/T5) and implemented grounding, decoding tuning, and post-generation validation to control hallucinations and quality. Also developed a "tech care" assistant chatbot with a custom Python orchestration/router layer (intent classification, context management, multi-step flows) and a structured testing/evaluation approach including expert review and automated checks.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer with cloud-native Python/Flask experience building high-throughput financial platforms (loan origination intelligent document processing and real-time fraud detection). Has scaled microservices on AKS with event-driven Azure messaging, delivered measurable performance gains (e.g., 700ms→180ms query latency; ~40% API improvements), and implemented strong security controls (OAuth2/JWT, Azure AD RBAC, audit logging, AES-256/TLS) for sensitive regulated data.”
Mid-level Cloud & DevOps Engineer specializing in AWS/Azure, Kubernetes, Terraform, and CI/CD
“IBM Power/AIX infrastructure engineer with hands-on production experience across Power8/Power9 frames, VIOS and HMC, including resolving a production LPAR outage caused by vFC mapping issues. Has operated PowerHA clusters for critical finance workloads, running quarterly failover tests and handling an unplanned failover triggered by a network adapter failure, then improving resilience with redundancy and monitoring automation.”
Senior Full-Stack Developer specializing in cloud-native web applications
“Full-stack engineer who built an oil & gas analytics dashboard backend using FastAPI, MongoDB, and Redis with a metadata-driven design for dynamic plotting. Shipped an LLM-powered chatbot (LangChain + tool/function calling) to let engineers query analytics in natural language, and also built a multi-step university chatbot workflow with Azure logging, confidence scoring, and human-in-the-loop review.”
Senior QA Automation Engineer specializing in test automation and CI/CD quality gates
“QA automation engineer focused on end-to-end quality for a CMS lien registration workflow, owning a Playwright-based regression suite covering high-risk paths (creation, amendments, cancellation, batch file validation). Demonstrated impact by catching a UI change that bypassed required-field validation pre-release, stabilizing flaky CI tests using network-response signals, and driving clearer acceptance criteria and observability improvements (request IDs in logs) through cross-functional collaboration.”
Mid-level DevOps/Cloud Engineer specializing in multi-cloud CI/CD and Kubernetes
“IBM Power/AIX infrastructure engineer who has owned a sizable production estate (50 Power servers / ~200 LPARs) spanning VIOS/HMC, SAN/NFS, and PowerHA clusters. Demonstrates strong incident leadership (LPAR outage + split-brain recovery) and a process-improvement mindset with measurable reductions in recurrence/MTTR, while also bringing modern DevOps/IaC experience (Jenkins, ArgoCD, Terraform, security scanning, canary/blue-green).”
Mid-Level Software Engineer specializing in Cloud Infrastructure and DevSecOps
“Production infrastructure engineer from Textron Systems who owned IBM Power/AIX 7.2 environments supporting manufacturing-critical automated RF test workloads. Deep hands-on experience with VIOS/HMC, DLPAR performance issues, SAN/vFC failures and failover recovery, plus modern DevOps practices (Azure DevOps CI/CD, Key Vault) and Terraform-based AWS infrastructure with remote state/locking and drift controls.”
Mid-level Full-Stack Java Developer specializing in microservices and cloud (AWS/Azure)
“Backend/full-stack Java engineer at PNC Bank specializing in real-time fraud detection systems. Built event-driven Spring Boot + Kafka microservices with PostgreSQL/Redis performance tuning, and shipped a production LLM-powered RAG feature for fraud analysts with strong guardrails (grounded internal data, structured prompts with references, human-in-the-loop) plus an evaluation loop using labeled historical fraud cases.”
Junior Software Engineer specializing in distributed systems, DevOps, and observability
“Built and launched a verified listings system for Burrow (student subleasing) after interviewing ~50 students about scam/fake listing concerns; chose a lightweight .edu-based verification approach to ship fast and then iterated with badges and clearer details, reducing churn from 15% to 7%. Also ran an LLM A/B test for auto-generating listing descriptions and improved trust/accuracy by updating prompts to prevent hallucinated details.”
Senior DevOps/Platform Engineer specializing in Kubernetes and cloud infrastructure
“DevOps/Infrastructure engineer with hands-on production experience building Jenkins CI/CD pipelines that provision Kubernetes infrastructure and process data into a MapR cluster. Uses Terraform to provision AWS resources (EC2, S3, VPC, subnets) with remote state in S3, separate environment state files, and code review/validation practices; targeting $135k base.”
Staff/Senior Cybersecurity Engineer specializing in threat intelligence, RMF/ATO, and Zero Trust
“Cybersecurity leader with 13 years in IT/cyber and 8 years in management, currently managing ~200 people while innovating explainable AI (XAI) for military/high-stakes decision-making. Experienced with large budgets, resource allocation, and investor engagement, and is motivated to build a proactive, future-focused cyber company centered on Zero Trust and human-overseen XAI.”
Junior AI/ML & Full-Stack Engineer specializing in LLMs and RAG systems
“Forward-deployed engineer who built a production AI drone-control chatbot that lets users fly a drone via natural language while viewing a real-time feed. Implemented RAG over drone SDK documentation (vector DB + top-k retrieval) and LoRA fine-tuning, with a focus on latency, token efficiency, and cost reduction, and regularly works with non-technical clients to integrate and explain AI system architecture.”
Senior Full-Stack Developer specializing in cloud-native FinTech and AI platforms
“Full-stack engineer with strong production ownership: built and operated a real-time transaction monitoring/fraud-alerting system using Java Spring Boot, Kafka, Docker, and AWS with CI/CD. Demonstrates metrics-driven operations (latency, stability, consumer lag, true/false positives) and reliability patterns for integrations (idempotency, retries/backoff, DLQs, reconciliation/backfills), plus modern React/TypeScript + Node/Postgres architecture experience.”
Mid-level Full-Stack Developer specializing in FinTech web applications
“Front-end engineer experienced modernizing legacy React/TypeScript applications, including building a highly customized navigation system controlled by feature flags and documenting it for cross-team adoption. Demonstrates strong performance optimization skills (profiling, provider refactors, memoization) and deep debugging ability, including resolving UI jank traced to Reach Router’s accessibility-driven focus behavior.”
Senior Full-Stack Software Engineer specializing in React/TypeScript and Spring/Go
“Software engineer/SME who owned customer-facing features in a tanker planning/scheduling domain, spanning UI, database migrations, and REST APIs. Drove major performance improvements by shifting complex pairing logic from a React/TypeScript frontend into a backend BFF (cutting load time from ~3 minutes to ~30 seconds) and led cross-team event-driven integrations using RabbitMQ and hexagonal architecture. Also built an internal OpenLayers-based mapping library adopted across multiple apps via Nexus.”
Junior Full-Stack Software Engineer specializing in TypeScript/React and microservices
“Software engineer who built and owned an internal workflow automation + analytics platform end-to-end (TypeScript/React/Node) with a microservices, RabbitMQ-based async architecture. Drove adoption by shipping iterative prototypes and prioritizing reliability/performance (Redis caching, query optimization), delivering ~30–35% latency improvements and ~30–40% reduction in manual operational work.”
Senior Frontend Engineer specializing in scalable consumer apps and micro frontends
“Frontend engineer focused on React/TypeScript dashboards for manufacturing-cycle analytics (downtime/wait time/cycle time). Has hands-on experience building reusable charting components (JSON-to-graph) with React ECharts, scaling data flows with Redux/RTK Query, and refactoring monolithic UI code into modular components while shipping on a ~3-week release cadence.”
Mid-level Full-Stack Developer specializing in cloud-native APIs and data workflows
“Built and owned end-to-end ordering and inventory/order management systems for a wholesale distributor, delivering an MVP quickly and iterating based on direct observation of daily users. Experienced with TypeScript/React + Node.js layered architectures and microservices using RabbitMQ, including real-world scaling issues (duplicates, backpressure) and observability practices (correlation IDs, structured logging).”
Mid-level Full-Stack Developer specializing in microservices and cloud-native web apps
“Frontend engineer who has led customer-facing web products end-to-end, with strong emphasis on scalable component architecture, design systems, and automated quality gates (CI + unit/integration/E2E). Experienced building complex React+TypeScript dashboards with thoughtful state separation and shipping fast via feature flags/canary releases while monitoring and optimizing real-world performance issues.”