Pre-screened and vetted.
Senior Full-Stack Software Engineer specializing in web platforms and AI/ML-enabled services
Senior Full-Stack Software Engineer specializing in Java/Spring and modern web apps
Mid-level Full-Stack Engineer specializing in Python, distributed systems, and FinTech
Senior Full-Stack Python Engineer specializing in cloud microservices and AI/LLM systems
Senior Software Engineer specializing in telehealth and e-commerce platforms
Senior Full-Stack Python Engineer specializing in trading and FinTech platforms
Senior Full-Stack Engineer specializing in React/TypeScript, React Native, and LLM-enabled products
Senior Full-Stack Software Engineer specializing in FinTech payments and risk systems
Mid-level Software Engineer specializing in full-stack and distributed backend systems
Senior Data Engineer specializing in cloud-native data platforms and streaming pipelines
Senior AI/ML Engineer specializing in LLM agents, RAG, and production ML systems
Engineering Manager specializing in payments, risk, and high-scale distributed systems
“Engineering leader/player-coach on a risk core transaction platform (payments/branded checkout) who led major migrations from a monolithic stack to microservices, including API contract redesign and performance improvements (reported ~500ms latency reduction). Experienced running high-stakes production incidents (upgrade-related outage/degradation) end-to-end with RCA and rollout-process changes, and has accelerated delivery via documentation/tooling (audit sign-off cycle reduced from ~3 sprints to ~1).”
Senior Software Engineer specializing in game platforms and player-facing systems
“Senior engineer with a rare mix of game-platform and mobile content-delivery experience: helped ship the Xbox 360 Party system and later architected the custom multi-catalog asset pipeline behind Netflix Stories. Particularly compelling for teams needing someone who can design scalable, low-memory, high-stability systems for live content across many titles and external partners.”
Intern/Student Software Engineer specializing in full-stack development, AI/ML, and quantitative finance
“Software engineering intern who built an internal AI-agent automation using the Gemini API to reduce manual CRM data entry, iterating prompts closely with analysts to address precision concerns. Also worked on a medical image-diagnostics LLM project involving fine-tuning and benchmarking multiple model approaches, and has quant/sales-trading experience building automated pricers for complex options and persuading sales teams to adopt them with ROI-focused metrics.”
Intern Software/AI Engineer specializing in LLM fine-tuning and agentic RAG systems
“Built and shipped an end-to-end LLM agent during an AT&T internship to automate network troubleshooting, with production-style reliability safeguards (timeouts/retries/fallbacks) and structured, state-machine orchestration; project won 3rd place in AT&T’s nationwide intern innovation challenge and was demoed to leadership. Also handled messy multi-partner data at Tencent by implementing schema validation/normalization, confidence-threshold fallbacks, and idempotent Python/ORM-based pipelines.”
Senior AI Research Engineer specializing in LLM agents and large-scale ML
“AT&T Labs builder who deployed a production multi-agent LLM system that lets engineers ask natural-language questions and automatically generates deterministic, schema-grounded Snowflake SQL (200–400 lines) to detect anomalies in massive wireless/network event data (~11B events/day). Experienced with LangChain and Palantir Foundry orchestration, RAG-based result interpretation, and rigorous evaluation/monitoring loops to continuously improve reliability.”
Staff Software Engineer specializing in distributed systems and platform architecture
“Built a production LLM-powered data ingestion workflow at Provi, an online alcohol marketplace, to clean and match millions of distributor inventory items against a product catalog. Their experience is strongest in applying LLMs to real-world, large-scale data operations with AWS Glue, S3, batching, API integration, human review, and drift detection.”
Senior Full-Stack Engineer specializing in serverless AWS and event-driven systems
“Backend/data engineer with experience at AWS and Intuit building and operating production serverless systems and data pipelines. Delivered an internal AWS TV video-processing platform using Step Functions/Lambda/S3/DynamoDB with strong reliability and cost controls, and built Glue-based ETL for compliance/risk events (Kafka to partitioned Parquet). Also modernized legacy compliance systems into Java/Node event-driven services and has demonstrated measurable SQL tuning impact (200s to 20s).”
Intern Full-Stack Software Engineer specializing in web apps and cloud-native systems
“Backend engineer who scaled a food delivery platform by migrating from a single-service architecture to Spring Cloud microservices with an API gateway and Kafka-based event-driven order pipeline. Reported outcomes include ~50% latency reduction, stable ~2K RPS throughput, and 99.8% uptime, with strong emphasis on safe migrations (dual writes, canaries, schema versioning) and security (JWT/RBAC/Postgres RLS).”
Intern Software Engineer specializing in full-stack, backend, and AI agent systems
“Backend engineer with Tesla experience who redesigned vehicle registration into a step-based, region-configured workflow across 4–5 microservices, enabling partial saves and reducing customer drop-off. Has hands-on experience scaling and securing Python/FastAPI APIs (OAuth2/JWT, CORS), migrating cold data from MySQL to MongoDB via Kubernetes CronJobs, and implementing RBAC/RLS with Supabase + Postgres.”
Senior Backend Engineer specializing in Python and AWS serverless systems
“Backend/data engineer with Amazon supply-chain experience building production serverless Python services and ETL pipelines on AWS (Lambda, API Gateway, S3, RDS, Glue). Has modernized legacy SAS jobs into Python with rigorous parity testing and phased migrations, and has delivered major SQL performance gains (minutes down to seconds) through indexing and partitioning.”