Pre-screened and vetted.
“Backend engineer focused on real-time, event-driven systems (Java microservices) handling high-frequency data with low-latency and reliability requirements. Strong in Kafka-based asynchronous architectures, Redis caching, JVM/query tuning, and scalable deployments on Docker/Kubernetes with Jenkins CI/CD; no direct ROS/robotics experience but has closely related distributed communication patterns.”
Senior Full-Stack Software Engineer specializing in SaaS platforms on AWS
“Full-stack engineer with strong DevOps/AWS experience who ships end-to-end React/TypeScript + Node/Python systems and operates them in production. Built an LLM-assisted recommendations workflow for a SaaS product with robust reliability controls (schema-validated JSON outputs, fallbacks, caching, monitoring) and measured impact via adoption, time saved, and override rates; also experienced delivering MVPs fast in early-stage startup ambiguity.”
Senior UAV/Robotics Engineer specializing in perception, sensor fusion, and localization
“Robotics software engineer working on GNSS-denied UAV localization using 5G PRS (OpenAirInterface + USRP B210) and multi-sensor fusion, with a published AIAA SciTech 2026 result achieving 1.5m RMSE on low-cost hardware. Also integrating a Vision-Language-Action model (SmolVLA) onto the Stretch 2 platform for language-assisted manipulation, leveraging ROS 2, imitation learning data collection with RGB-D, and simulation in Gazebo/MuJoCo for sim-to-real deployment.”
Senior Site Reliability Engineer specializing in cloud observability and incident response
“Backend engineer experienced in evolving high-scale legacy on-prem systems into cloud-native, event-driven microservices on AWS/Kubernetes (noted peak traffic ~1.5M QPS). Strong focus on reliability engineering and operational excellence—SLO-driven observability, GitOps/canary rollouts, chaos testing, and preventing cascading failures (e.g., retry-storm mitigation).”
Junior Full-Stack Software Engineer specializing in automation and web development
“Built Meet.AI end-to-end and made concrete architecture/performance decisions (RPC with type-safe integration; SSR + query prefetching for instant data display). Also created a Python tool at Abbott to resynchronize Ansible inventories and eliminate manual intervention by scheduling it in a Jenkins pipeline; has hands-on Docker/microservices experience including serving a pretrained LLM.”
Junior Software Engineer specializing in cloud administration and Python/ML
“Backend/data engineer with hands-on production experience across Azure and AWS: built FastAPI + PostgreSQL services with Azure AD OAuth2/JWT auth and strong reliability patterns (timeouts, retries, correlation IDs). Delivered AWS Lambda/ECS solutions with Terraform/CI-CD and cost controls (SQS buffering, reserved concurrency), and built/operated AWS Glue ETL pipelines into Redshift while modernizing legacy SAS reporting into Python microservices with parity testing.”
Intern AI/ML Engineer specializing in LLMs, RAG, and agentic automation
“Built and deployed production NLP/LLM systems including a multilingual (5-language) health misinformation detection pipeline with latency optimization (batching/quantization/caching) and explainability (gradient-based attention visualizations). Experienced orchestrating end-to-end AI workflows with Airflow and Prefect, and partnering with customer support ops to deliver an AI agent for ticket summarization and priority classification with clear, measurable acceptance criteria.”
Mid-Level Full-Stack Software Engineer specializing in automation and platform reliability
“Built and owned invoice automation and alerting products at Neuralix, automating multi-site electricity invoice ingestion from PDFs into validated JSON with strict schema enforcement and LLM-based validation (reported ~98% compliance). Delivered zero-manual processing at 200+ invoices/month and ~5x faster throughput, and designed a domain-driven alert lifecycle to reduce noisy notifications and improve operational response.”
Senior/Lead Unity Developer specializing in mobile games, AR, and multiplayer integrations
“Unity gameplay engineer with AAA experience who built a highly configurable weather/day-night system (clouds/rain/sun-moon/stars) that influenced core gameplay decisions (vehicles, time-of-day, farming/animal needs). Also has hands-on multiplayer experience with Photon Fusion (including client-backend communication and physics sync troubleshooting) and has set up CI/CD and build pipelines.”
Junior Data Engineer specializing in LLM agents and RAG pipelines
“Built and deployed “ApartmentFinder AI,” a multi-agent system using Google ADK, Gemini, and Google Maps MCP to automate apartment shortlisting and commute-time analysis, cutting a 45–70 minute user workflow down to ~30 seconds. Also has strong delivery/process chops from serving as an SDLC Release Coordinator, managing 52+ releases and reducing SDLC issues by 84%.”
Junior AI Engineer & Full-Stack Developer specializing in AI agents and RAG systems
“Full-stack TypeScript/React/Next.js builder who created an end-to-end customer-facing product (AI Job Master) that generates personalized outreach from resumes and job descriptions. Demonstrates strong product + engineering ownership with rapid MVP iteration, instrumentation-driven prioritization, and pragmatic reliability patterns (microservices, queues, correlation IDs, retries) while tackling a key AI challenge: user trust and output consistency.”
Mid-level Java Full-Stack Developer specializing in Spring microservices and React
“Full-stack engineer with recent enterprise experience building Spring Boot/Spring Cloud microservices on AWS (Lambda, S3, DynamoDB) and a React/TypeScript frontend. Has hands-on experience solving microservice communication timeouts via API Gateway/load balancing and implementing centralized JWT-based security, plus performance work for large data workloads using indexing, caching, and async processing.”
Intern Software Engineer specializing in full-stack development and IAM automation
“Built and owned a Python/FastAPI backend for a custom translation service used in a showroom application, integrating DynamoDB and connecting the service to a SPA/Next.js frontend. Has exposure to Kubernetes-based deployments and GitHub Actions CI/CD, and contributed to planning an on-prem to cloud/SaaS migration at Sherwin-Williams by gathering requirements across multiple plants/factories.”
Intern Software Engineer specializing in IAM, iOS, and AI security
“Early-career engineer who built a self-directed production-grade security scanning/analysis pipeline that normalizes multi-scanner results, correlates CVEs, and uses an LLM to generate exploit hypotheses—then hardened it for real-world reliability (timeouts, confidence scoring, feature flags, graceful degradation). Also integrated a real-time audio ML model into Discord/Zoom and debugged intermittent latency/dropouts across Python inference, virtual audio drivers, and network jitter; experienced with IAM integrations (Entra ID/Salesforce) and cloud tooling (AWS/Docker/Kubernetes).”
Mid-level Python Backend Developer specializing in APIs, automation, and data pipelines
“Backend Python engineer with end-to-end ownership of secure financial data systems integrating banking/credit/payment platforms, including automated ingestion and reconciliation of large financial statements. Built modular Dockerized Django REST services with pandas-driven validation/normalization and Postgres/Mongo persistence, and supported a phased migration from legacy VM services to AWS containers with stateless refactors and parallel-run integrity checks (run IDs/checksums). Works closely with platform teams on GitOps/CI readiness and deployment coordination (e.g., ArgoCD-managed sync policies).”
Mid-level Software & ML Engineer specializing in agentic LLM systems and ML infrastructure
“Built and deployed an LLM-to-SQL automation system in a closed/internal environment, using a retriever–reranker–validator architecture on Kubernetes with strong security controls (semantic + rule-based validation and RBAC), achieving 99% uptime and cutting manual query time ~40%. Also worked on genomic sequence classification and semantic search workflows, orchestrating data prep with Airflow, tracking/deploying with MLflow, and optimizing distributed multi-GPU training on a university Kubernetes cluster.”
Junior Robotics Engineer specializing in computer vision and mobile manipulation
“Founding Robotics Research Engineer at Streamline Robotics building precision-agriculture automation: integrated FANUC + PLC harvesting with a Farm-ng Amiga (Jetson) platform using ROS2 Visual SLAM for GPS-free greenhouse navigation. Developed real-time YOLOv8 tomato detection/ripeness estimation for selective harvest and configured Cognex D900 3D inspection, plus redesigned FarmBot Genesis XL and built an automated imaging/labeling pipeline for growth tracking and adaptive watering.”
Mid-level Full-Stack Software Engineer specializing in cloud, data pipelines, and GenAI
“Full-stack engineer currently building an employee management system end-to-end with React, Node/Express, and PostgreSQL, including JWT auth and RBAC. Previously worked at TCS on large-scale State Bank of India web applications, applying Redis caching, server-side pagination/filtering, and async job offloading to improve performance and reliability.”
Entry-level Robotics Engineer specializing in ROS2 autonomy and motion planning
“Robotics software engineer who led an energy-aware persistent monitoring project on TurtleBot4/ROS2, building the full stack from simulation and motion control to an energy consumption model and control algorithm implementation. Developed custom ROS2 Python nodes (battery + cmd_vel logging), integrated with Nav2, and handled multi-robot coordination via DDS while troubleshooting network/QoS issues. Also built and tuned a human-aware navigation behavior using Gazebo-based testing and data-driven threshold optimization.”
Mid-level Data Scientist specializing in NLP, recommender systems, and ML deployment
“At Provenbase, built and shipped a production LLM-powered semantic search and candidate matching platform (RAG with GPT-4/Gemini, multi-agent orchestration, Elasticsearch vector search) to scale sourcing across 10M+ candidate records and 1000+ data sources. Drove sub-second performance, cut LLM spend 30% with routing/caching, and improved recruiting outcomes (+45% sourcing accuracy; +38% visibility of underrepresented talent) through bias-aware ranking and tight collaboration with recruiting stakeholders.”
Mid-level Software Engineer specializing in backend engineering and applied AI workflows
“Backend engineer with fintech/transaction-processing experience who built and optimized a Spring Boot + PostgreSQL + AWS service handling money transactions, resolving peak-traffic latency via query/index and connection pool tuning. Shipped an LLM-driven risk-flagging workflow integrated via a FastAPI Python service, owning prompt design, validation guardrails, monitoring, and human-in-the-loop escalation to reduce false positives and improve precision over time.”
Mid-Level Full-Stack Developer specializing in React, React Native, and cloud data systems
“Full-stack engineer who built a checklist configuration/task execution system using Next.js App Router + TypeScript, with a React Native app consuming the execution UI via WebView. Was the only full-stack developer at a very small startup (CTO/CFO/CEO team), owning feature delivery plus client-facing on-call debugging, and has hands-on Postgres modeling and query optimization experience.”
Mid-level Site Reliability Engineer specializing in cloud infrastructure and Kubernetes
“Backend/infra-focused engineer who owned production systems for distributed ML experimentation (hyperparameter tuning across a cluster with GPU scaling, custom scheduling, and checkpoint-based fault tolerance). Also built and operated a low-latency log validation service using queued async workflows with idempotency, retries/backoff, and strong observability, plus experience building resilient Selenium-based browser automations for complex multi-step web flows.”
Mid-level Software Engineer specializing in AI, full-stack development, and RAG systems
“Built and owned a production RAG search/Q&A platform at Data Integrity First for a client with a large, hard-to-search document library, deployed on AWS. Drove major adoption gains by adding source attribution (users trusted answers more) and improved system performance with guardrails, logging, and iterative chunking/OCR normalization—cutting fallback rate from ~22% to under 10%.”