Vetted AWS Professionals

“ML/AI engineer focused on production-grade model reliability: built a monitoring and validation framework to detect drift, trigger anomaly alerts/retraining, and maintain consistent performance for device intelligence workflows at scale. Strong MLOps background with Python pipelines, Docker/Kubernetes deployments, Airflow orchestration, and real-time monitoring dashboards; experienced partnering with product managers to deliver business-facing insights.”

“ML/AI engineer with hands-on ownership of production systems spanning classical ML fraud detection and GenAI agent workflows. At Fidelity, they built an end-to-end fraud platform that improved review queue Precision@K by 15-20% while reducing false positives 10-15%, and they also shipped RAG-based agent systems that cut manual workflow effort by 30-40%.”

“AI-native software engineer who uses agentic development as a core workflow, including a three-agent setup for planning, validation, and implementation. In their most recent role, they acted as the lead orchestrator for AI agents, with a strong emphasis on production safety, architectural control, and rigorous validation.”

Hansraj Pabbati

Screened

Senior Software Engineer specializing in AI/LLM systems and cloud backend platforms

Remote, CA8y exp

“Built and owned an end-to-end AI-powered natural-language-to-SQL deployment within Oracle OCI/Autonomous Database, including enrichment pipelines, RAG-based retrieval, SQL generation APIs, and post-launch monitoring. Stands out for combining LLM production engineering with strong guardrails, stakeholder management, and operational rigor around accuracy, latency, hallucination mitigation, and reliability.”

Nilesh Dixit

Screened

Executive AI engineering leader specializing in agentic AI and enterprise platforms

San Francisco, CA24y exp

“Bay Area engineering leader and startup co-founder with a rare mix of deep hands-on architecture experience, large-scale people leadership, and cross-functional product ownership. He helped launch GE Digital's industrial IoT efforts, holds multiple patents in the space, has scaled teams to 60-70 people, and has led both enterprise platform modernization and AI startup product development.”

“Healthcare-focused full-stack/platform engineer with recent hands-on experience in Go, React, Python, Kubernetes, and AWS. They have worked in high-reliability, compliance-heavy environments, driving infrastructure modernization, internal operational tooling, and observability improvements that reduced troubleshooting friction for clinician platform and support teams.”

Nicholas Gunder

Screened

Director of Engineering specializing in FinTech, SRE, and AI platforms

Remote, USA25y exp

“Engineering leader with deep hands-on experience across people management, product ownership, SRE, and architecture, currently leading a 15-person senior engineering team he largely built himself. He is actively applying AI/LLMs to both internal developer productivity and customer-facing financial support workflows, including an LLM ledger chatbot with automated guardrail evaluation in a regulated environment.”

“Engineering leader with experience rebuilding a 35-person organization after acquisition, spanning operations, QA, and multiple software teams. Combines hands-on technical judgment in areas like search, AI chatbot integration, and AWS operations with strong organizational leadership, including process modernization, quality embedding, and customer-feedback-driven AI product improvement.”

“SRE-focused engineer with experience at Sony Interactive Entertainment productionizing high-throughput LLM/agentic systems on Kubernetes, including GPU-aware autoscaling and warm-pool strategies to manage latency and cost under traffic spikes. Demonstrates strong incident response using Prometheus/Grafana + Jaeger tracing (e.g., resolving recursive agent loops and restoring 99.9% availability within minutes) and partners closely with sales/customer teams through PoV demos and developer workshops.”

“Backend engineer from Palantir who built and productionized an enterprise LLM-based document intelligence/search platform, evolving it into a hybrid lexical+vector retrieval system. Emphasizes reliability and cost control via strict LLM gating, robust fallback paths, and evaluation frameworks (e.g., MMLU/BLEU), plus disciplined migration practices (feature flags, dual-writes, shadow reads) to ship changes safely at scale.”

“Senior growth/partnership leader operating at the intersection of cloud, AI, and creator/gaming ecosystems. Has driven >20% QoQ revenue growth and double-digit user growth via ecosystem partnerships, design-partner pilots, and referral loops, and reports shortening sales cycles 25–30% through a strong telecom/enterprise network (Verizon, Dish, T-Mobile, Scotiabank; earlier Cisco/Ericsson).”

“AI/ML engineer who has shipped both a safety-critical mental health RAG chatbot (Mistral 7B + Pinecone) with automated faithfulness/toxicity monitoring and a deep Q-learning investment recommendation engine at Lincoln Financial Group. Strong in production MLOps and orchestration (AWS Lambda/CloudWatch/SageMaker, Docker, AKS) and in translating regulated-domain requirements (clinical reliability, fiduciary duty) into measurable model constraints and monitoring.”

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

“Infrastructure/operations engineer with hands-on IBM Power/AIX administration (LPAR/DLPAR, HMC, RMC) and PowerHA cluster failover experience, plus modern DevOps tooling across CI/CD, Kubernetes/Helm, and IaC (Terraform/CloudFormation/Ansible). Emphasizes controlled change management, drift prevention via Git-as-source-of-truth, and observability practices using Prometheus/Grafana.”

“Active in the venture ecosystem as a Rogue Women's Fund fellow and angel investor, with memberships in Gaingels and Angel Squad (HustleFund). Interested in founding a company to leverage extensive experience, and evaluates ideas through market need and economic viability of the target population.”

“Data engineer at Plaid who built greenfield, end-to-end real-time transaction pipelines and FastAPI data services for fraud detection and analytics, handling millions of events per day. Strong focus on reliability and data integrity via Great Expectations validation, Airflow-based monitoring/SLAs, quarantine/staging patterns, and robust external data ingestion with schema versioning and backfills (reported 50% fewer anomalies and ~40% fewer failures).”

Sumaya Shakir

Screened

Executive Technology Leader specializing in SaaS platforms, data ecosystems, and product engineering

24y exp

“Technology leader who drove end-to-end modernization at Dogtopia—building a proprietary SaaS POS/CRM and operations platform plus an AI-powered customer app—using OKR-driven roadmaps and Agile/DevOps delivery. Previously at GE, led a cloud-native AWS data fabric re-architecture with strong security/governance (RBAC, classification, encryption, lineage, virtualization), cutting processing time 60%+ and enabling AI workloads tied to $400M in business value.”

Pranav Puranik

Screened

Senior AI Engineer specializing in LLMs, RAG, and multimodal NLP

Austin, TX5y exp

“Built a production LLM/RAG assistant for insurance/health claims agents that ingests 100–200 page patient PDFs via OCR (migrated from local Tesseract to Azure Document Intelligence) and delivers grounded claim detail retrieval plus summaries with PII/PHI guardrails. Experienced orchestrating large workflows with Celery worker pipelines and AWS Step Functions (S3-triggered, Fargate-based batch inference/accuracy aggregation), and collaborates closely with non-technical SMEs (claims agents/nurses) through shadowing, iterative demos, and SME-defined evaluation.”

Akhilaa Sonduri

Screened

Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps

Cambridge, MA2y exp

“Full-stack engineer with experience at HubSpot, Accolite, and an early-stage USC alumni startup (Workup). Built and shipped end-to-end workflow automation features (dynamic input configuration with strict schema validation) driving ~25% faster configuration, and delivered an AI interview customization feature in a high-ambiguity startup setting that increased adoption by ~40%. Comfortable operating production systems on AWS with CloudWatch observability and CI/CD, and has built real-time web apps with caching/indexing for performance.”

Feras Alsaiari

Screened

Senior Software Engineer specializing in AWS data platforms and event-driven systems

4y exp

“Capital One engineer leading the architecture and delivery of a large-scale AWS Glue/Spark/Delta Lake batch messaging pipeline that decoupled batch from real-time flows, added multi-region failover and automated retries, and delivered ~40% AWS cost savings with ~3x performance gains. Currently building an LLM-powered Slack bot using RAG to automate message investigations by querying CloudWatch, Snowflake, and internal documentation with privacy-aware masking of NPI/PII.”

Manjory saran

Screened

Senior Backend & Infrastructure Engineer specializing in cloud-native distributed systems

5y exp

“LLM infrastructure engineer who built a production-critical real-time personalization and memory retrieval system for a user-facing product, adding <100ms P99 latency while improving relevance ~20–25% and holding SLA through 3x traffic. Experienced designing tiered retrieval backends (Redis + vector store), deploying on Kubernetes with autoscaling/circuit breakers, and running rigorous observability, incident response, and agent evaluation (shadow traffic, A/B tests, regression/replay).”

Paiman Nodoushani

Screened

Executive CTO specializing in AI-powered transformation for enterprise SaaS

New York, NY35y exp

“Former Cisco professional who successfully pitched and got funding for adding virtualization to access routers to enable third-party application development, framing the opportunity with clear revenue upside and risk management. Highly interested in AI—especially agent-based development—and believes it lowers the barrier to building and shipping new products with small, high-caliber teams.”

Rojin Bakhti

Screened

Junior Software Engineer specializing in Edge AI and ML deployment

San Diego, CA3y exp

“Qualcomm engineer building Android applications that run on Qualcomm AI accelerators, with hands-on experience in C++ concurrency, chipset stress testing, and power/performance tuning. Has deployed on-device AI models and built deployment/log post-processing workflows using Docker/Kubernetes and CI/CD; interested in translating this embedded AI/performance background into robotics (perception/real-time systems).”