Pre-screened and vetted.
Junior Software Engineer specializing in cloud-native microservices
“Backend engineer (Nokia) who designs and migrates cloud-native microservices at scale, including a secure low-latency system handling 500k+ daily transactions. Strong in Kubernetes/OpenShift operations, CI/CD standardization, and production security (OAuth2/JWT/RBAC) with SOC2-aligned controls and zero critical security incidents. Demonstrated expertise in safe migrations (canary/blue-green, dual writes, reconciliation) and concurrency correctness in real-time systems.”
Director-level Engineering Leader specializing in enterprise SaaS and cloud-native platforms
“Engineering leader/player-coach who modernized a legacy C#/SQL Server system to Snowflake + Python on GCP, enabling ~30x scale and supporting hundreds of millions of transactions per day per customer. Strong in architecture tradeoffs (Snowflake vs Databricks), production reliability (New Relic, logging/alerting), and lightweight process improvements like a rigorous Definition of Done and structured PR reviews.”
Mid-level Data Engineer specializing in multi-cloud real-time and batch data pipelines
“Data engineer with healthcare domain experience who owned 100M+ record pipelines end-to-end (Kafka/Kinesis/ADF → PySpark/dbt validation → Spark SQL transforms → Snowflake/Power BI serving). Built production-grade reliability practices (Airflow orchestration, CloudWatch/Grafana monitoring, pytest + contract/regression tests, idempotent ingestion/backfills) and delivered measurable improvements: 35% lower latency and 40% better query performance.”
Senior Full-Stack Java Developer specializing in cloud-native microservices
“Full-stack engineer with experience building secure, cloud-native document/workflow platforms handling high-volume customer and medical data across microservices on Kubernetes. Demonstrated impact improving performance via event-driven AWS architectures (Lambda + DynamoDB Streams) and strengthening compliance/security for S3-stored documents using IAM and KMS. Has delivered end-to-end APIs and UIs using Java/Spring Boot with Angular/React, plus Docker and CI/CD.”
Junior Full-Stack Engineer specializing in AI applications and scalable web platforms
“Full-stack engineer with customer-facing delivery experience who built and deployed a multi-platform social media automation product (Next.js/Node/MongoDB) and optimized it using BullMQ/Redis background jobs, retries, and rate limiting for reliable posting at scale. Also delivered an AI-powered false-positive analysis service in a cybersecurity context, resolving production pipeline stalls via log-driven debugging, parallelization, caching, and LLM guardrails.”
Senior Machine Learning Engineer specializing in MLOps and NLP/GenAI
“Built a production LLM-agent framework for a startup that performs daily financial/trading analysis by combining live market data with internal tools, including a centralized memory module to prevent context drift and reduce hallucinations. Also implemented an Airflow-orchestrated retail price forecasting pipeline deployed to AWS endpoints, scaling parallel workloads via Kubernetes Executor and validating systems with rigorous functional + LLM-specific metrics and cross-team collaboration.”
Intern Software Engineer specializing in backend systems and data engineering
“Backend/AI engineer who has built and shipped two products: Know Founder (Python/SQL/AWS) scaling to 2,000+ users in the first month, and Unifr (unifr.online), an AI search visibility engine that queries multiple LLMs and turns responses into structured brand insights. Strong in production reliability/performance (Redis caching, indexing, precomputation) and in designing agentic workflows with guardrails, validation, retries, and human escalation.”
Mid-level Full-Stack Software Engineer specializing in Generative AI
“Full-stack engineer who shipped an end-to-end speech capability for an LLM chatbot UI, integrating OpenAI APIs and publishing via Google Apigee with client documentation. Has experience operating deployments with Jenkins/Kubernetes/Docker and monitoring with Datadog, and has worked in an innovation-center environment building rapid prototypes under ambiguity with tight stakeholder feedback loops.”
Mid-level Data Engineer specializing in real-time pipelines and cloud data platforms
“Backend engineer with hands-on experience building secure Python/Flask services (sessions, JWT, RBAC) and optimizing PostgreSQL/SQLAlchemy performance, including custom SQL using CTEs/window functions profiled via EXPLAIN ANALYZE. Also integrates LLM features via OpenAI/Azure into backend systems and improves scalability with RabbitMQ-driven async processing, caching, and multi-tenant data isolation patterns.”
Junior Data Analyst specializing in financial and operational analytics
“Analytics professional with experience at KPMG turning messy operational and financial data from SQL Server and AWS S3 into clean reporting datasets and automated Python workflows. They combine SQL, Python, Power BI, and experimentation methods to deliver stakeholder-aligned KPI dashboards and marketing performance insights with a strong focus on data integrity and reproducibility.”
Intern AI/ML Engineer specializing in full-stack and data systems
“Built an LLM-powered customer segmentation agent during a Chewy internship, consolidating Snowflake data into a knowledge graph so non-technical marketing users could query customer cohorts in natural language. Stands out for combining agent/tooling design with rigorous data engineering practices, including schema audits, imputation, validation layers, and idempotent pipelines on messy large-scale datasets.”
Mid-level Business Analyst specializing in finance, insurance, and data analytics
“Business/data analyst with experience at KPMG and Liberty Mutual, focused on financial reporting, data quality, and analytics automation. Has built SQL and Python workflows for large transaction datasets, reduced manual reporting effort by 15+ hours per week, and translated ambiguous business questions into standardized KPIs and Power BI dashboards used for decision-making.”
Mid Software Engineer specializing in backend systems and FinTech
“Backend engineer with experience spanning regulated financial systems at Oracle Financial Services and early-stage product building at Apli.ai. Has owned production onboarding infrastructure end-to-end, improved reliability through strong observability and incident response, and also built AI-backed backend workflows using AWS, Bedrock, and RAG.”
Senior Data Scientist and AI/ML Engineer specializing in GenAI and cloud ML
“ML/AI engineer with hands-on experience owning systems from experimentation through deployment and monitoring, including a Bank of Montreal project that improved timely interventions by 12%. Also brings GenAI/RAG experience with evaluation and safety guardrails, plus clinical NLP pipeline work extracting medication data from notes for patient risk prediction.”
Mid-level Full-Stack Software Engineer specializing in AI and document automation
“Backend/AI infrastructure engineer focused on production-ready LLM systems and distributed workflows. They described building a RAG-based multi-step agent with strong reliability controls, evaluation loops, and graceful degradation that improved latency by 30%, retrieval accuracy by 15%, and reduced support workload by 40%.”
Mid-level AI/ML Engineer specializing in FinTech and retail ML systems
“ML-focused candidate with strong Wells Fargo experience building production fraud systems and internal GenAI tools for fraud analysts. Stands out for measurable impact in fraud detection—raising recall from 71% to 88%—while also demonstrating hands-on depth across streaming infrastructure, MLOps, LLM/RAG implementation, and Python service architecture.”
Mid-level Python Backend Engineer specializing in cloud-native and AI-powered systems
“Backend/AI engineer who has shipped an LLM-powered enterprise support-ticket agent at Comcast, building a production-grade microservices pipeline (FastAPI, SQS, Redis) with strong observability (OpenTelemetry/Splunk/Prometheus/Grafana) and reliability patterns (async, caching, circuit breakers, idempotency). Demonstrated quantified impact at scale—processing 10k+ tickets/day while improving response SLAs and routing accuracy through evaluation and human feedback loops.”
Mid-level Full-Stack Developer specializing in cloud-native enterprise systems
“Candidate brings a pragmatic, production-focused approach to AI-assisted software development, using AI as a pair programmer and conceptually applying multi-agent workflows across coding, testing, and review. They stand out for putting strong guardrails around AI usage—manual review, testing, SonarQube, peer review, and keeping critical logic manual—to improve speed without compromising security or code quality.”
Junior Full-Stack Java Developer specializing in enterprise web applications
“Full-stack engineer with hands-on experience building an internal telecom order-tracking/dashboard platform at T-Mobile across React, Spring Boot, and PostgreSQL. Stands out for owning features end-to-end, from scalable frontend architecture and TypeScript patterns to API design, query optimization, CI/CD, and post-launch monitoring in AWS CloudWatch.”
Senior Software Engineer specializing in backend systems and data platforms
“Software developer who uses AI pragmatically across the full stack to accelerate coding, testing, debugging, and documentation while maintaining strong human oversight. Stands out for treating AI output like any other code source—reviewing for architecture fit, security risks, performance, and standards before integration—and for coordinating multiple AI tools across backend, frontend, and test workflows.”
Mid-Level Full-Stack Software Engineer specializing in React, Node.js, and cloud-native systems
“Data engineer/backend engineer with healthcare domain experience at Centene, where they owned an end-to-end claims processing pipeline handling over 1 million monthly records. They combine Python/SQL pipeline work with API and event-driven service development, and cite a measurable 35% reduction in incident detection time through automated monitoring and validation.”
“Backend engineer focused on productionizing LLM systems: built a FastAPI-based RAG and multi-agent automation platform deployed with Docker/Kubernetes, prioritizing safe execution and reduced hallucinations. Experienced in refactoring monolithic ML services with feature-flagged incremental rollouts, and implementing JWT/RBAC plus row-level security (e.g., Supabase) for secure, scalable APIs.”
Senior Software Engineer specializing in distributed systems and cloud platforms
“Software professional with 13 years of experience across Canada and India, now seeking a first US role in California. Has practical experience applying LLMs and IDE agents like Cursor, ChatGPT, and Gemini to streamline engineering documentation workflows, especially automating Jira/Confluence process work to reduce manual effort and errors.”
Staff Full-Stack Engineer specializing in API-driven web platforms and distributed systems
“Highly agent-centric builder who uses Codex daily to generate and manage full application repos, including Next.js CRUD apps, GitHub automation, and AWS lifecycle scripts to avoid long-lived cloud artifacts. They also experiment with multi-agent workflows for parallel development and correctness checking, showing strong practical fluency with emerging AI-native software development patterns.”