Vetted Terraform Professionals

“Backend engineer who built a high-stakes, privacy-first platform at be Still Analytics for survivors of domestic violence, emphasizing anonymity, security, and reliability. Experienced with GenAI backends (LangChain + AWS Bedrock) including RAG to prevent hallucinations, plus cloud-native scaling (Docker/Kubernetes) and cost-saving migrations from legacy VMs to serverless (30% reduction).”

“Backend/data engineer with aerospace telemetry and reporting experience across RTX and other orgs, spanning Python/FastAPI microservices, AWS serverless/containers, and AWS Glue-to-Redshift analytics pipelines. Has led legacy modernization with parallel-run parity validation and incremental rollout, and demonstrates strong operational ownership (monitoring, incident response, and cost optimization).”

“Backend/data engineer with hands-on production experience building Python/Django APIs on PostgreSQL and delivering AWS serverless + containerized architectures (API Gateway/Lambda, IaC, CI/CD, secrets/config). Has operated AWS Glue pipelines ingesting S3 log/3rd-party data with schema evolution monitoring, modernized legacy batch logic into API-based services via parallel-run parity testing, and improved Postgres query performance by several seconds; prefers fully remote work and targets $120–130k base.”

“Built and shipped a production real-time content moderation platform for Zoom/WebEx-style meetings, combining Whisper speech-to-text with fast NLP classifiers and REST APIs to flag hate speech, bias, and HIPAA-related content under strict latency constraints. Demonstrates strong MLOps/infra depth (Airflow, Kubernetes, Terraform/Helm, observability) and a pragmatic approach to reducing false positives via threshold tuning, context validation, and hard-negative data—while partnering closely with compliance and product stakeholders.”

“IBM Power/AIX engineer who has owned a 150+ LPAR AIX 7.x estate with VIOS/HMC/vHMC and PowerHA in production, including real outage and failover recoveries. Also brings modern DevOps/IaC experience—built Jenkins pipelines deploying to AKS and implemented Terraform on AWS with remote state, locking, and drift management.”

“Full-stack intern at Rebel who owned backend work on a cross-platform music platform using Python/Django with MongoDB, implementing user-focused REST APIs end-to-end. Also built CI/CD pipelines (Jenkins/GitHub Actions) to containerize and deploy to AWS, and has experience integrating Kafka-based real-time event processing with reliability and observability practices.”

“Backend engineer with Accenture and EY experience building multi-tenant financial/compliance platforms in Python/Flask. Strong in performance and scalability work across SQLAlchemy/PostgreSQL (EXPLAIN ANALYZE, indexing, N+1 fixes) and in reliability improvements using Celery + Redis. Has integrated external AI model APIs for document extraction/invoice validation with robust background processing, retries, and output cleaning.”

“Healthcare-focused ML/LLM engineer who built a production hybrid RAG workflow to automate prior authorization by retrieving from medical guidelines/historical cases (FAISS) and generating grounded rationales for clinicians. Strong in operationalizing ML with Airflow/Kubeflow/MLflow on SageMaker, optimizing latency (ONNX/quantization/async), and reducing hallucinations via evidence-only prompting; also partnered closely with clinical ops to deploy a readmission prediction tool used in daily rounds.”

“CloudData engineer who productionized an LLM assistant for a warehouse/logistics customer by wrapping it as a versioned, containerized API with guardrails, deterministic post-processing, and full observability. Experienced diagnosing real-time RAG/agentic incidents (latency spikes and confident-wrong answers) using trace-based isolation, replay in staging, retrieval tuning, and canary releases. Regularly runs technical demos/workshops and partners with sales on security/IAM, SLAs, and pilot rollouts to drive adoption.”

“Engineering leader who modernized infrastructure by migrating a ~100-server co-location setup to AWS/GCP with IaC, auto-scaling, and fault-tolerant design, reducing hardware upgrade burden. Also led a key analytics architecture shift from MySQL to ClickHouse to enable highly granular ad revenue attribution and profitability insights, while scaling the dev org from 2–3 to ~12 with stronger CI/testing and review processes.”

“Built a contract and customer documentation retrieval solution for Urban Studio, designing a RAG + Elasticsearch hybrid search stack (RRF + cross-encoder reranking) with a strong emphasis on chunking/data quality and hallucination reduction. Experienced in diagnosing LLM workflow issues via observability traces and tailoring technical demos to developer concerns like reliability and high concurrency.”

“Built and shipped a production AI booking/quoting system for a Spanish-speaking cleaning business serving English-speaking customers, covering the full booking and payment flow and generating bilingual SEO/AEO content. Uses Gemini/Genkit with multi-agent orchestration (ADK/MCP, LangChain) and a production stack on Vertex AI + Cloud Run + Terraform, with analytics wired from Google Analytics to BigQuery for measurable agent performance.”

“Full-stack .NET/Azure engineer with end-to-end ownership of policy management microservices (React/TypeScript + C#/ASP.NET Core + Kubernetes) delivering significant performance and quality improvements (e.g., response time -35%, defects -30%, CSAT +18%). Also productionized an AI-assisted analyst workflow using Azure OpenAI with a RAG pipeline on Azure Cognitive Search, including rigorous prompt versioning, guardrails, and measurable impact (review time -40%, errors -55%). Led incremental legacy modernization via Strangler Fig and dual-write migrations with zero production regressions.”

“Full-stack/AI engineer who has shipped production systems spanning real-time analytics dashboards and an internal LLM-powered knowledge assistant. Experienced with RAG pipelines (embeddings/vector DB, semantic retrieval, query rewriting) plus evaluation loops and guardrails, and builds observable Kafka-based data pipelines monitored with Prometheus/Grafana.”

“Cloud/infrastructure engineer with strong production operations background across AWS, Azure, and Kubernetes, supporting 30+ enterprise workloads for ~40,000 users. Demonstrated incident leadership (hybrid AKS-to-AWS routing outage) with a reported 60% MTTR reduction, plus hands-on CI/CD (Jenkins) and Terraform-based IaC for AWS (VPC/EC2/EKS). Lacks direct IBM Power/AIX/PowerHA experience but emphasizes transferable ops and troubleshooting skills.”

“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.”

“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).”

“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.”

“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.”

“Backend/data engineer who has built production AI video generation services on AWS using a hybrid serverless + container architecture (FastAPI, Lambda, ECS, Postgres/Redis) with strong reliability practices (auth, retries/timeouts, structured logging, CloudWatch + Slack alerting). Also delivered AWS Glue ETL pipelines with schema evolution handling and modernized a legacy SAS healthcare reporting workflow to Python with parity validation and parallel-run migration.”

“Founding engineer at a startup building LLM/agentic workflows for public-safety customers, with hands-on experience delivering a hybrid on-prem + secure cloud solution to meet strict compliance needs. Implemented OpenTelemetry observability for multimodal agentic systems behind closed networks and used the resulting traces to optimize prompting/token usage for customer-specific security integrations. Regularly runs technical workshops and supports pre/post-sales by translating integration feedback into product roadmap decisions.”

“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.”

“Built and productionized a RAG-based semantic search system for video-derived data, focusing on measurable success metrics (p95 latency, reliability, cost/request) and strong observability (prompt versions, retrieved docs, tool calls, token usage). Experienced in diagnosing real-time issues in LLM/agentic workflows and in supporting go-to-market efforts through tailored technical demos, rapid POCs, and post-close onboarding.”