Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in MLOps, NLP, and Generative AI
“Built and deployed a production LLM-powered text-to-SQL/document intelligence chatbot on AWS that lets non-technical business users query complex enterprise databases in plain English. Demonstrates deep practical expertise in schema-aware prompting, embeddings-based schema retrieval, SQL safety/validation guardrails, and rigorous offline/online evaluation with human-in-the-loop approvals for risky queries.”
Senior Backend/Cloud Developer specializing in AWS serverless and legacy modernization
“AWS-focused backend/data engineer with hands-on production experience building serverless APIs (Lambda/API Gateway) secured with Cognito/JWT, deploying via Terraform + CI/CD, and managing secrets with Secrets Manager/Parameter Store. Also built AWS Glue ETL from S3 to RDS with schema evolution and data-quality controls, modernized a monolith into microservices using parallel testing, and delivered major SQL performance gains (minutes to seconds) while owning incident response for batch pipelines.”
Mid-level Software Engineer specializing in distributed real-time systems
“Backend engineer focused on real-time, event-driven distributed systems (Node.js/TypeScript) with strict latency and reliability requirements. Deep hands-on experience debugging concurrency issues and designing resilient workflows (idempotency, circuit breakers, compensating actions) with strong observability; familiar with ROS/ROS2 concepts and confident ramping into robotics integrations.”
Mid-level Data Engineer / Software Engineer specializing in streaming and cloud data platforms
“Backend engineer with deep Kafka/FastAPI microservices experience who redesigned a notification pipeline to cut end-to-end latency from ~5s to ~3s (including custom partition assignment and consumer tuning). Led a high-stakes ClickUp-to-Oracle migration of 1M+ records using idempotent ETL, reconciliation, and shadow deployment to achieve >99% integrity with zero downtime, and has hands-on production security implementation with Django/DRF (JWT + RBAC).”
Mid-Level Full-Stack Engineer specializing in real-time systems and FinTech
“Backend engineer with hands-on experience modernizing a real-time logistics/tracking platform from a tightly coupled polling architecture to a service-oriented/microservices design using Node.js and WebSockets. Emphasizes contract-first FastAPI development, defense-in-depth security (JWT/OAuth, RLS/Supabase), and safe incremental migrations with feature flags and strong observability, delivering sub-second updates and improved performance under peak load.”
Mid-level AI Engineer and Data Scientist specializing in LLM agents and RAG systems
“Built a production-grade LLM evaluation and regression system that stress-tests models across hundreds of iterations, combining LLM-as-judge, semantic similarity, statistical metrics, and rule-based checks, with results delivered via stakeholder-friendly HTML reports and dashboards. Experienced orchestrating multi-agent RAG workflows using LangChain/LangGraph and event-driven GenAI pipelines in n8n integrating OCR, speech-to-text, and external APIs, with strong emphasis on reliability, observability, and explainable failures.”
Mid-level Software Engineer specializing in cloud-native microservices, DevOps, and SRE
“Built and productionized an LLM-enhanced version of the WeDAA platform to auto-generate microservice architecture diagrams and support code generation from user prompts, including a practical solution for non-overlapping canvas object placement via coordinate templates. Experienced in diagnosing agentic workflow failures using AWS Strands agents with feature-flagged debug logging, and frequently supports sales through tailored demos and POCs to drive adoption.”
Mid-Level Software Engineer specializing in backend systems, cloud, and applied LLM/NLP
“Applied LLMs to classify long nonprofit mission statements into 8 segments without labeled data, using an ensemble of clustering/embedding methods plus zero-shot RoBERTa/BART and a Tree-of-Thought prompting pipeline with LLM-as-judge evaluation (Gemma). Also built LangChain/LlamaIndex agentic RAG workflows including a text-to-SQL data analysis assistant grounded on DB schema with retries and performance optimizations on an HPC cluster.”
Mid-level Data Scientist specializing in Generative AI and LLMOps
“Built a production-grade, semi-automated document recognition and classification system for large volumes of scanned PDFs, starting from little/no labeled data and handling highly variable scan quality. Deployed on AWS using SageMaker + Docker and orchestrated on EKS with a microservices design that scales CPU-heavy OCR separately from GPU inference, with strong reliability controls (validation, fallbacks, retries, readiness probes).”
Mid-level Software Engineer specializing in cloud-native backend and distributed systems
“Backend/full-stack engineer with experience building customer-facing contact-center automation (agent assignment) and internal editorial/data operations APIs for life-sciences ontology management. Strong in microservices and event-driven systems (Spring Boot + Kafka), third-party integrations (Genesys/Five9), and pragmatic iteration via MVP scoping, tight stakeholder demos, and observability-focused reliability.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native apps and ML services
“Software engineer who deployed and stabilized a real-time analytics platform at Senecio Software, focusing on production reliability, observability, and performance under load. Experienced debugging issues spanning distributed services and networking (e.g., tracing timeouts to packet loss from misconfiguration) and extending Python (FastAPI/Django) APIs for customer-specific analytics features in a configurable, maintainable way.”
Mid-level AI Data Engineer specializing in GenAI, RAG, and cloud data pipelines
“LLM/agentic AI builder who deployed a production ITSM automation agent on Google ADK integrating ServiceNow and FreshService, with strong safety guardrails (human-approval gating and runbook-only command execution) and rigorous evaluation (500 synthetic tickets; 80%+ false-positive reduction). Also partnered with finance to deliver an AI agent that automated invoice/SOW retrieval and monthly reporting to account managers, reducing manual back-and-forth.”
Intern Software Engineer specializing in backend systems, cloud, and AI agents
“Built and productionized an LLM-based appointment management agent, implementing RAG with Redis and LangGraph plus multi-agent intent handling and rule-based conflict guardrails to prevent double-booking under high load. Experienced in real-time diagnosis of agentic workflow failures using logs/traces and state inspection, and in driving adoption via interactive developer demos and sales-aligned custom customer scenarios.”
Mid-level Solutions Consultant / Full-Stack Developer specializing in APIs, SQL, and cloud systems
“Builder with hands-on security hygiene experience from developing a helpdesk portal handling sensitive payment/invoice data, focusing on RBAC, least-privilege integrations (QuickBooks/Atera), and tightening API authorization to prevent cross-account access. Also built personal projects integrating Twilio/Callkeep/Supabase/OpenAI with strong key management and defensive handling of real-world API/network failure modes; holds an ISC2 certification and is actively deepening cloud security skills.”
Junior AI Data Engineer specializing in Azure Databricks lakehouse and GenAI RAG systems
“Backend/applied AI engineer from Cloud Rack Systems who built production GenAI/RAG and data platforms on Azure/Databricks at enterprise scale (2.5M records/day). Known for making LLM systems behave like deterministic services via strict retrieval contracts, citation-based validation, and strong observability—shipping a knowledge assistant used daily by 50+ users while driving hallucinations near zero and materially improving latency and cost.”
Junior Software Developer specializing in Oracle APEX and enterprise integrations
“Oracle Software Developer (2+ years) at C3 Business Solutions, a consulting firm building and maintaining ERP applications across Oracle APEX/FDI/Fusion/EBS/OCI. No formal game QA experience yet, but demonstrates practical QA-adjacent skills (test planning, debugging via logs, and detailed bug reporting) and is explicitly looking to transition into a QA Engineer role.”
Senior Java Full-Stack Developer specializing in cloud-native microservices
“Backend Java developer who built an end-to-end upcoming payments feature: Spring Boot/Hibernate microservices with MySQL query/index optimization and Kafka event publishing, plus a web UI timeline component enabling users to view, skip, and edit scheduled payments with clear status indicators.”
Mid-level Full-Stack Engineer specializing in Java/Spring, React, and AWS cloud platforms
“Full-stack/product-leaning engineer in logistics and high-traffic portals who ships production AI features: built an AI-assisted shipment status Q&A system using Pinecone + GPT-4 and a high-volume Python ingestion pipeline (500K+ records/day), delivering 35% fewer support tickets and cutting resolution time from 11 to 4 minutes. Also led a legacy Angular-to-React/TypeScript rebuild that boosted Lighthouse performance from 60 to 90, and has hands-on AWS EKS operations experience including resolving a 3x traffic scaling incident.”
Mid-level Full-Stack Java Engineer specializing in Generative AI and cloud microservices
“Full-stack engineer who has delivered production customer analytics/dashboard features using Next.js App Router + TypeScript on the frontend and Java Spring Boot microservices on the backend. Demonstrates strong production ownership (monitoring latency/error rates/adoption) plus hands-on performance work across React rendering and Postgres query/index optimization, and has implemented Temporal-like durable workflows with retries and idempotency.”
Mid-Level Software Engineer specializing in distributed systems and AI agent workflows
“Software engineer with enterprise CPQ/CRM/ERP integration experience (Argano) who owned an end-to-end pricing preview capability deployed on AWS Kubernetes with Jenkins CI/CD and full observability (Prometheus/Grafana). Also built an AI-native research agent using LangChain + Chroma to filter academic papers, reporting ~15 hours/week saved for a professor.”
Mid-level AI Engineer specializing in RAG, conversational AI, and agentic systems
“Built and deployed a production RAG-based clinical decision support assistant at MedLib, focused on fast, trustworthy answers from large medical documents. Demonstrates deep practical experience improving retrieval accuracy (semantic chunking + metadata-aware search), controlling hallucinations with grounded generation and thresholds, and adding clinician-requested citations using chunk metadata, with evaluation driven by healthcare professional review.”
Junior Full-Stack & LLM Engineer specializing in AI agents and cloud document intelligence
“Backend engineer specializing in event-driven/serverless systems and Python/FastAPI APIs. Built a scalable PDF-to-structured-data pipeline on AWS (S3, Lambda, Step Functions, Textract, DynamoDB, SNS) with strong observability (p50/p90/p99) and reliability patterns (idempotency, retries/DLQs), and has led zero-downtime migrations using feature flags, dual writes, and incremental rollouts.”
Junior AI/Full-Stack Software Engineer specializing in ad automation and LLM systems
“Full-stack engineer with deep ad-tech/marketing automation experience, building production tools that reduce programmatic ad waste and improve search ads performance. Shipped and operated AWS-deployed, Dockerized systems with Postgres/Redis and strong observability (Datadog/OpenTelemetry), and delivered measurable impact (25k campaigns processed, 50k sites negated, 3–4 hours/week saved). Built scalable abstractions for multi-platform ad integrations, enabling rapid onboarding of additional clients.”
Junior Full-Stack Software Engineer specializing in distributed systems and data pipelines
“Backend engineer with hands-on experience building distributed data and API platforms (Kafka + Neo4j on Kubernetes), including processing 3M+ NYC taxi trip records and achieving sub-second graph analytics queries. Strong focus on reliability and performance in Python/FastAPI systems—async refactors, caching, timeouts/retries, feature-flagged rollouts, and JWT/RBAC security for production services.”