Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in Generative AI and RAG systems
“Currently at ProShare and reports building an AI/LLM-powered system deployed to production, aimed at helping with status-related difficulties and reducing misunderstandings across transactions. Also cites prior collaboration at Porsche with marketing teams, focusing on translating marketing goals into technical requirements and communicating solutions clearly to non-technical stakeholders.”
Entry-level Full-Stack Software Engineer specializing in backend, cloud, and AI systems
“Software engineer with hands-on experience across platform modernization, production AI agents, and workflow automation. They led a monolith-to-microservices migration that increased deployment speed from weekly to daily, built a self-healing GPT-powered browser agent with an 85% autonomous recovery rate, and founded/ran ZapDash, where they hardened Kafka-based integrations against silent data loss.”
Mid-level Full-Stack Engineer specializing in Healthcare IT and SaaS
“Backend/data engineer with healthcare/medical-device experience who scaled a HIPAA-constrained local data platform to 50k users and 1B+ records, boosting processing from <500 to ~50k datapoints/sec using sharding, indexing, and SQL over Parquet (DuckDB). Strong security and reliability focus (JWT/RLS, least privilege, heavy unit/E2E testing) and a TypeScript specialist who uses type design to eliminate edge-case failures.”
Mid-level Systems Software Engineer specializing in distributed cloud infrastructure
“Backend-leaning full-stack engineer in fintech/payments who shipped an end-to-end Stripe payments + webhook system for a financial microservices platform, emphasizing ledger accuracy via idempotency, transactional writes, retries, and DLQs. Also delivered a real-time React/TypeScript payment status dashboard informed by user interviews, and improved production performance by 35% p95 latency through PostgreSQL tuning and Redis caching on AWS.”
Senior Full-Stack AI/ML Engineer specializing in MLOps and GenAI
“Senior backend/data engineer who has built and maintained HIPAA-compliant, real-time clinical FastAPI services on AWS, orchestrating ML/LLM and vector DB calls with strong reliability patterns (auth, timeouts/retries, graceful degradation, idempotency). Also delivered AWS IaC/CI-CD (Terraform/Helm/GitHub Actions) across EKS/Lambda/SageMaker and built Glue/Spark ETL with schema evolution and data quality controls, plus demonstrated large SQL performance wins (15 min to <9 sec) and hands-on incident ownership.”
Junior Backend Engineer specializing in cloud APIs and AI-enabled systems
“Built and shipped "OnCall Copilot," a production Slack-based RAG assistant that answers on-call questions from runbooks and postmortems with citations using a FAISS vector index. Emphasizes reliability and measurable performance via strict guardrails ("no evidence, no answer"), evaluation metrics, drift monitoring, and operational hardening with Docker, logging, health checks, and offline fallback.”
Mid-Level Software Developer specializing in API development and test automation
“Self-taught frontend developer with React/TypeScript project experience and strong QA background. Contributed as a QA tester on a Skunkworks web app by refining large story tickets, defining happy-path/edge test cases, and setting sprint metrics; also improved a legacy PHP web app by modularizing SFTP bulk upload code and enhancing page navigation.”
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.”
Intern Full-Stack Engineer specializing in AI-powered products
“Software engineer (internship experience) who built and owned an AWS serverless multi-user “challenge” feature end-to-end (UI + REST APIs + DynamoDB + deployment), delivering measurable gains in latency (-30%), debugging time (-50%), and join drop-offs (~-30%). Also productionized a multilingual RAG-based QA system with vector retrieval and guardrails, improving accuracy to ~85% and driving ~20% DAU growth.”
Entry-Level GenAI/LLM Engineer specializing in agentic systems and RAG
“LLM/AI agent engineer with consulting/contract experience (Kanhaiya Consulting LLC) who deployed a production AI agent to automate BIM list workflows end-to-end—from database understanding and data cleaning to automated visualizations/dashboards. Worked around restricted real-time data access by generating synthetic data and improving outputs via supervised fine-tuning, and uses AWS-based LLMOps observability (Opic/OPEC) plus hybrid retrieval (vector+BM25 with reranking) to optimize relevance, latency, and cost.”
Junior Data Scientist specializing in statistical modeling and machine learning
“AI Researcher with production experience building a real-time computer-vision detection pipeline augmented by an LLM-based verification layer to cut false positives (~78%) and reach ~90% real-world accuracy. Also partners cross-functionally with Product/Sales/Marketing to shape AI feature prioritization and market positioning using analysis and interactive dashboards.”
Senior Full-Stack Developer specializing in Node.js/TypeScript, cloud, and data engineering
“Frontend/fullstack lead who inherited a messy psychological app with production issues, drove a rapid stabilization (2–3 weeks) and major performance/architecture overhaul (Redux Toolkit, memoization, caching, lazy loading, CDN offload to S3/CloudFront). Also owns delivery and infrastructure practices (multi-env, Docker, GitHub Actions CI/CD, AWS ECS + load balancing) and led a 1-week POC for an AI-powered trucking management system (app.neblo.ai).”
Junior Full-Stack/Product Engineer specializing in Next.js, TypeScript, and AWS backends
“Full-stack engineer with startup-style end-to-end ownership, recently shipping a production dashboard at Find Me LLC using Next.js App Router/TypeScript with Supabase + Azure Blob Storage for secure asset/document uploads. Strong server-first React performance mindset and hands-on Postgres modeling/query optimization (EXPLAIN ANALYZE), plus experience building resilient AWS event-driven workflows with idempotency, retries, and DLQs.”
Senior Unity Developer specializing in gameplay, multiplayer, and backend integration
“Unity gameplay engineer who has shipped mobile and Meta Quest VR titles, leveraging DOTS/ECS for large-scale war/rts-style scenes and mobile performance. Built multiplayer features using Photon PUN 2 with PlayFab matchmaking/backend and implemented live network debugging/recovery strategies. Also prototyped an AI/LLM-assisted pipeline for generating and validating gameplay/level content via structured JSON with fallbacks and caching to control reliability and cost.”
Senior AI Engineer specializing in machine learning, GenAI, and MLOps
“Built an end-to-end agentic population health strategy copilot for healthcare leadership, turning broad chronic disease questions into structured, evidence-backed strategy briefs. Stands out for combining healthcare domain knowledge with production-grade GenAI implementation, including LangGraph orchestration, Databricks/MLflow deployment, human review, and quality gates focused on citations, metrics, risks, and safety.”
Mid-level Software Automation Engineer specializing in AI and healthcare IT
“Built production automation systems spanning Python integrations, analytics sync pipelines, and internal workflow apps. Notably automated an architectural site inspection process end-to-end with an app, database, and letter generation engine that reduced workload by 20%, and improved reliability of a Botpress/Supabase/Airtable cron integration by eliminating recurring rate-limit failures through batching.”
Junior Software Developer specializing in LLMs, RAG pipelines, and web applications
“Backend engineer (Encore) who led the evaluation and redesign of a high-volume, low-latency real-time retrieval/ranking and inference platform on AWS, shifting from tightly coupled services to a modular architecture for better fault isolation and independent scaling. Strong focus on production reliability, observability, and security (JWT/RBAC, multi-tenant scoping, Postgres/Supabase RLS), with disciplined migration playbooks (feature flags, shadow traffic, dual writes/reconciliation).”
Junior Machine Learning Engineer specializing in Document AI and LLM-powered workflows
“Built and owned a customer-facing Document Intelligence Service for legal contract analytics at Noasis Digital, delivering extraction/summarization with careful accuracy controls (confidence thresholds, versioned deployments, production logging). Also developed a React/TypeScript document review app and internal QA dashboard, and has hands-on microservices experience with async messaging (RabbitMQ), timeout tuning, and centralized structured logging for reliability at scale.”
Mid-Level Software Engineer specializing in full-stack and mobile development
“Frontend-leaning engineer who shipped an end-to-end map-based discovery feature in a React Native mobile app, integrating location-based REST APIs with strong UX polish (loading/empty/error states) and cross-platform performance fixes. Also has experience building a Python backend with JWT auth and layered service structure, plus prior infrastructure work setting up centralized logging and monitoring.”
Junior Full-Stack Software Engineer specializing in AI workflows and LLM integrations
“Built and productionized an AI-assisted merchant onboarding automation workflow for Kort Payments, replacing slow manual underwriting document review with structured extraction, cross-document validation, and human-in-the-loop guardrails. Emphasizes reliability via scenario-based testing, repeatability checks, and deep observability (timestamped logs), plus incremental rollout with legacy fallback to prevent regressions.”
Junior AI Engineer specializing in LLM systems, RAG, and scalable cloud AI
“Built and shipped production LLM agents for real-time, high-concurrency conversational systems, including a RAG-based pipeline with dynamic multi-provider routing and failover that achieved 99.99% reliability and sub-800ms latency. Also architected a UAV telemetry chatbot with tool-calling (anomaly detection/summarization), strict schema validation, and robust eval/monitoring loops, cutting tool-call errors by 30% and reducing operational costs by 90%.”
Senior Data Scientist & Machine Learning Engineer specializing in computer vision and production ML
“PhD in computer engineering who has built production-oriented ML/NLP systems for space-weather prediction using Spark-based ETL on noisy satellite sensor logs. Strong in entity resolution and semantic search—fine-tuned E5 embeddings with contrastive learning and deployed to Pinecone, improving top-5 retrieval precision by 25%—and emphasizes scalable, observable pipelines with Airflow, Docker, and CI/CD.”
Senior DevOps Engineer specializing in multi-region AWS/GCP cloud infrastructure
“Backend/data engineer with strong AWS production experience spanning FastAPI microservices and large-scale data pipelines. Has delivered containerized Python services on EKS with Terraform/Helm/GitHub Actions, implemented robust auth/secrets practices, and owned ETL reliability (Glue/S3/Redshift) including incident response and idempotent reruns. Demonstrated SQL tuning on 50M-record ETL workloads to remove SLA misses and improve reliability.”
Mid-level Backend Engineer specializing in high-scale systems and LLM pipelines
“Open-source-focused TypeScript/JavaScript engineer who built a lightweight Node.js utility library to standardize LLM-agent message formatting, tool invocation, and safe schema-validated JSON outputs. Emphasizes composable abstractions, real-world performance profiling/benchmarks, and strong community feedback loops (GitHub issues, structured errors, logging hooks). Also did research at Syracuse University on converting natural language into structured JSON with validation layers.”