Pre-screened and vetted.
Junior Software Engineer specializing in cloud infrastructure, observability, and full-stack systems
“Built and productionized a predictive maintenance system (predictEngineLife) estimating Remaining Useful Life for PW4000 turbofan engines from large-scale, noisy telemetry—emphasizing modular pipeline design, deterministic preprocessing, and strong observability/guardrails. Also has hands-on experience diagnosing multi-agent LLM customer-support workflows (schema/state issues, fallback paths, regression tests) and has led developer workshops (GDG Pune) while partnering with sales teams on technical discovery and POCs.”
Intern AI Engineer specializing in LLM agents, RAG, and scalable cloud deployment
“AI/LLM engineer at GPT integrators who built a production multi-agent enterprise workflow integration system, tackling hard problems in agent orchestration, layered memory, and custom RAG over enterprise/user data. Also built an education-focused agent solution integrating with Canvas, Zoom, and email to automate classroom admin tasks, and is currently applying agentic AI to insurance underwriting workflows in collaboration with underwriters.”
Senior Linux Systems Engineer specializing in hybrid cloud and DevOps automation
“Cloud/infrastructure engineer from ASM Research supporting federal healthcare systems, operating multi-cloud (AWS/Azure/GCP) environments at ~2000-server scale. Deep hands-on experience with Terraform/Ansible IaC, PR-based governance (Atlantis), and secure CI/CD (OIDC/least privilege), with concrete incident response wins and HA/failover testing improvements. Not an IBM Power/AIX specialist but comfortable translating virtualization/partitioning and ops practices to new platforms.”
Senior Data Engineer specializing in cloud lakehouse and streaming data platforms
“Data platform/data engineer with cross-industry experience in banking and healthcare, building cloud-native lakehouse architectures across AWS/Azure/GCP. Has owned high-volume (millions of records; TB/day) pipelines with strong data quality automation (dbt/Great Expectations), observability (Grafana/Prometheus), and real-time streaming (Kafka/Spark) for fraud monitoring; also delivered an early-stage migration from SQL Server to BigQuery with 40% batch latency reduction.”
Mid-Level Software Engineer specializing in FinTech payments and event-driven microservices
“Backend/data engineer focused on fintech payments and fraud systems, owning real-time Kafka-based reconciliation pipelines end-to-end (~13k tx/day). Built audit-friendly validation/reconciliation (SQL + Python), kept lag to seconds, and cut errors ~20%, while also shipping Spring Boot APIs with Redis caching and strong idempotency/versioning. Has early-stage startup experience standing up payment services on AWS with Docker + GitHub Actions and production monitoring/incident handling.”
Senior DevSecOps Engineer specializing in Azure cloud infrastructure and CI/CD
“GCP-focused database/infrastructure engineer with hands-on production support for Cloud SQL and Firestore, spanning provisioning, IAM, scaling, backups, and performance tuning. They also described supporting a hybrid GCP architecture for a monolithic on-prem PostgreSQL workload and resolving a major latency incident by tracing cascading failures and fixing indexing issues.”
Junior Backend Software Engineer specializing in cloud and AI systems
“Built and shipped LLM-enabled decision systems focused on real production reliability rather than chatbot demos, including a multimodal radiology retrieval platform with 28% relevance gains and 35% lower latency. Also architected a 4-agent employee analytics workflow with structured outputs, traceable orchestration, and strong safeguards for messy real-world data.”
Mid Software Engineer specializing in systems, CI/CD, and applied machine learning
“Engineer at Syniti who uses AI tools pragmatically to speed development while maintaining quality through rigorous validation, code reviews, and CI/CD. Most notably, they leveraged AI-assisted testing to increase test coverage from 10% to 70%, and they are actively exploring more advanced agent-based development workflows.”
Mid-level Software Engineer specializing in e-commerce and supply chain platforms
“AI-focused developer who has built several practical AI products, including EchoMate, a voice-agent system designed to act as a proxy for doctors and support patients when physicians are unavailable. Also has experience with multi-agent/API-based workflows in a solar suitability project, showing interest in applying AI across both healthcare and climate-related use cases.”
Senior AI/ML Engineer specializing in Generative AI, LLMs, and RAG systems
“AI/ML engineer with hands-on experience shipping production systems across fintech, travel, and legal use cases. They’ve built end-to-end chatbot, generative content, and RAG solutions on AWS with CI/CD, monitoring, and guardrails, including a loan application platform that generated $3,000 in sales in its first month.”
Mid-level Software Engineer specializing in backend systems and AI-driven platforms
“Backend-focused developer with primary experience in Python, Node.js, databases, and API development. Served as the sole backend engineer on a customer dashboard project, owning database review, API endpoint creation, and coordination with frontend developers for integration.”
Junior Full-Stack Engineer specializing in AI and distributed systems
“Built and owned a hackathon project (Gritto) with a Python/FastAPI backend that routes user text through a sequence of Gemini agents to produce structured JSON outputs. Has hands-on production deployment experience using Docker/Docker Compose, GitHub Actions CI/CD, AWS App Runner, MongoDB, and secrets management (Doppler + migration to AWS Secrets Manager), plus implemented a chat-like experience via multiple HTTP requests when SSE wasn’t viable.”
Mid-Level Software & Infrastructure Engineer specializing in cloud, distributed systems, and AI
“Backend/data engineer who helped evolve Bitnimbus LLC’s Kafka-as-a-service MVP from a monolith into an event-driven distributed system, using careful design, parallel rollouts, and idempotent event handling to maintain correctness. Also built production-grade API and database security (JWT scopes, rate limiting, explicit Postgres policies/RLS-style controls) and improved Prometheus monitoring by eliminating false outages via heartbeat metrics and windowed aggregation.”
Intern Full-Stack Software Engineer specializing in web apps, cloud microservices, and AI tooling
“Robotics/embedded candidate who built an IoT smart shoe for visually impaired users, implementing real-time obstacle detection with ultrasonic sensors and haptic feedback on Arduino. Has practical ROS experience (RViz/Gazebo) and improved reliability in distributed systems by hardening an Arduino-to-ROS serial protocol with framing, strict parsing, and sensor-noise filtering; also containerized ROS environments with Docker for reproducible simulation and onboarding.”
Mid-Level Software Engineer specializing in Java/Spring microservices and cloud event-driven systems
“LLM/agentic-systems practitioner who has repeatedly taken LLM-driven pricing/decision services from prototype to production using pilots, guardrails, observability, and staged rollouts. Demonstrates strong real-time incident troubleshooting (dependency timeouts, cached fallbacks) and post-incident hardening (isolation/async/alerts), and also supports go-to-market via developer workshops, technical demos, and sales-aligned POCs.”
Mid-level Data Engineer specializing in cloud data platforms and AI/ML analytics
“Backend/data engineer in healthcare who built an AWS-based clinical analytics platform from scratch (DynamoDB/S3/Airflow/dbt) with sub-second clinician query goals, 99.9% uptime, and HIPAA-grade controls (KMS encryption, IAM RBAC, audit trails). Also modernized ML delivery by replacing a manual 4-hour deployment with a 30-minute Docker/GitHub Actions CI/CD pipeline using parallel runs, parity testing, and rollback, and caught critical EHR data edge cases (date formats/timezones) that could have impacted patient care.”
Senior Python Developer specializing in FastAPI, Django, and cloud-native web applications
“Backend engineer working on Plumas Bank’s digital modernization, building a FastAPI-based loan origination/processing system with OAuth2/JWT security, AWS Lambda-driven PDF document generation to S3, and MongoDB integration. Has led a legacy workflow migration to a new microservice using dual-write/dual-read and monitoring, and emphasizes multi-tenant isolation via layered API controls plus row-level security.”
Intern Data Scientist specializing in robotics localization and SLAM
“Robotics/embodied-AI practitioner who built a TurtleBot3 LiDAR-fingerprint localization pipeline end-to-end (autonomous data collection + multi-head NN) achieving ~30 cm error in a 10x10 m space. Also has industry experience at Infineon building large-scale production data/AI pipelines and rapidly fixing a deployed recommendation system by correcting upstream data normalization, improving accuracy by 20%+.”
Mid-Level Software Engineer specializing in React front-end and web APIs
“Backend-leaning full-stack engineer from Valcom who maintained Django/PostgreSQL services for mass-notification/paging servers used by education/commercial/government customers. Notable for hardening authentication and reliability (JWT refresh + rotation tokens, WebSockets/EventStream) and for modernizing a legacy Ext.js/PHP stack into a React + Django architecture with strong CI/testing and production incident ownership.”
Mid-level AI & Machine Learning Engineer specializing in Generative AI and MLOps
“Built a production GPT-4/LangChain/Pinecone RAG “AI Copilot” at Northern Trust to automate financial report generation and analyst Q&A over internal structured (SQL warehouse) and unstructured policy data. Focused on real-world production challenges—grounding and latency—achieving major speed gains (seconds to milliseconds) via MiniLM embedding optimization and Redis caching, and implemented rigorous testing/evaluation with MLflow-backed metrics while aligning compliance and finance stakeholders for deployment.”
Mid-level Machine Learning Engineer specializing in LLMs, GenAI, and Computer Vision
“LLM/agent engineer who built a production multi-agent research automation system using LangGraph (planner, retriever with FAISS, supervisor, evaluator) with structured outputs and citation tracking for traceable reports. Emphasizes reliability and operations—LangSmith-based observability, multi-level testing, hallucination mitigation, and latency/cost controls—plus prior experience as a Computer Vision Software Engineer at Deepsight AI Labs working directly with non-technical customers.”
Entry-Level Software Engineer specializing in distributed systems and backend infrastructure
“Built and operated an end-to-end customer-facing "Record Platform" web product as both engineer and primary user, focusing on reliability and correctness in core flows like search and checkout. Implemented a TypeScript/React frontend with a multi-service backend and Kafka-based event-driven architecture, and created internal tooling to automate risky ops like Kubernetes TLS certificate rotation with k6 load/chaos testing (including HTTP/2 and HTTP/3 validation).”
Mid-level Full-Stack Developer specializing in Java/Spring Boot, React, and cloud microservices
“Backend/platform engineer with hands-on ownership of Kubernetes GitOps delivery (GitHub Actions + Argo CD) on AWS EKS, including progressive rollouts and reliable rollback across interdependent microservices. Built a Python/FastAPI ML-driven document-processing service (PostgreSQL + S3) to complement existing Spring Boot systems, and implemented Kafka streaming pipelines with Schema Registry plus Prometheus/Grafana observability. Also supported a hybrid cloud-to-on-prem migration for compliance/latency with phased rollout and incremental PostgreSQL migration.”
Mid-level AI/ML Software Engineer specializing in data pipelines, BI dashboards, and computer vision
“Graduate Assistant Intern at Friends University who built and deployed a GenAI-driven requirement understanding system that automates extraction and semantic grouping of technical requirements from large unstructured documents. Demonstrates strong LLM engineering rigor (golden datasets, regression testing, post-processing validation) and production-minded delivery using LangChain/LlamaIndex orchestration, FastAPI microservices, Docker, and cloud deployment.”