Vetted AWS Professionals

Thazim Banu Shaffee

Screened ReferencesStrong rec.

Engineering Manager specializing in payments, risk, and high-scale distributed systems

San Jose, CA14y exp

“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).”

Jared Alessandroni

Screened ReferencesStrong rec.

Executive CTO specializing in AI, cloud platforms, and scaling SaaS products

21y exp

“NYC-based startup founder/CTO who sold products to Omnicom and Sprinklr, then built an AI-powered cultural insights engine inside Omnicom using AWS Lambda + ML to process ~1M items/day and reached ~$1MM ARR in year one. Former senior leader at Sprinklr managing 200+ people globally, delivering enterprise martech solutions with SLAs and high-reliability social data pipelines (Twitter firehose).”

“McKinsey practitioner who built and deployed production LLM systems for consultants/clients, including a Power BI-integrated multi-agent chatbot (RAG + text-to-SQL + formatting) with custom Python orchestration, verification loops, and a 100+ case eval set achieving ~95% consistency. Also delivered a taxonomy-mapper agent that standardized inconsistent labeling for C-suite stakeholders, cutting a process from >2 weeks to <30 minutes through demos and business-focused communication.”

“Project lead who partners with PM and customers to gather requirements, adjust project plans, and deliver new functionality that drives customer satisfaction and revenue. Has experience building features end-to-end and presenting successful technical demos to engineering and management audiences; no stated experience with LLM/agentic systems.”

“CRO/operator with experience at both AWS and a rapidly scaling Hawaii-based startup (Mana'olana International), focused on building lightweight but scalable operating systems. Known for implementing QBR/OKR rhythms, capacity/territory planning, KPI dashboards, and ROI-tied funding controls, and for mentoring founders through GTM accelerator work (Blue Startups) using a minimum-viable-process approach.”

“Built and productionized a real-time enterprise RAG pipeline to improve factual accuracy and reduce LLM hallucinations by grounding responses in constantly changing internal knowledge bases (policies, manuals, FAQs). Experienced in orchestrating end-to-end ML workflows (Airflow/Kubernetes), handling messy multi-format data with schema enforcement (Pydantic/Hydra), and maintaining freshness via streaming incremental embeddings plus batch refresh. Also delivers applied ML solutions with non-technical teams (marketing/CRM) for segmentation and personalized engagement.”

“Embodied AI/robotics-focused ML engineer who built a real-time assistive Braille device by coupling transformer OCR with an Arduino-controlled electromechanical Braille cell, solving tight latency and hardware-integration constraints. Has recent work on geometry-grounded world models and a real-time 4D reconstruction foundation model (Any4D), and delivered measurable impact at Voxel AI by building a scalable headless simulation + synthetic data pipeline that improved a safety-critical algorithm’s recall by ~16%.”

“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.”

“Google backend engineer with strong experience in large-scale identity, membership, and access-control systems. Notable work includes reconciling customer IDs across 2B+ roster records and leading a 0-to-1 Drive sharing feature to classify external users as crossover members, with a strong emphasis on correctness, rollout safety, and low-latency service design.”

“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.”

“Meta engineer who has shipped both user-facing full-stack product work and internal AI agent systems at production scale. Most notably built AuditFixer, an agentic remediation pipeline that fully automated audit-fix workflows, cut turnaround from 6-7 hours to under 1 hour, and has already produced 30+ landed diffs, while also owning the Llama API evaluation flow launched for thousands of developers.”

“Backend engineer who helped redesign and refactor Forma’s backend during an app rewrite, emphasizing modularity, maintainability, and A/B testing support while delivering feature parity on a quarter-long timeline. Led a careful database migration using parallel databases with schema differences, validating integrity via staging and SQL checks, and has experience debugging subtle computer-vision overflow edge cases.”

“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).”

“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”

“Operations/engineering leader from Poly who optimized a professional headset portfolio by aggressively prioritizing technical debt and consolidating HW/SW platforms (down to 2 each), accelerating time-to-market by ~6 months and enabling 3–6 month variant cycles. Also drove AI-enabled quality improvements by leveraging JIRA bug data to automate test case creation and expand coverage, while aligning engineering and product management around MVO delivery.”

Abhinav Bandaru

Screened

Junior Data Scientist specializing in Generative AI and agentic LLM systems

San Jose, CA1y exp

“LLM/agentic-systems builder who has shipped production tools for investment research and procurement insights, including a company screener that processes thousands of conference-listed companies using FireCrawl + Google Search + Gemini. Demonstrates strong orchestration expertise (LangGraph multi-agent graphs), performance optimization (async/batching to sub-30s), and pragmatic reliability/evaluation practices with stakeholder-friendly UX (real-time cost tracking and model/parameter toggles).”

Akshitha Singireddy

Screened

Junior Software Engineer specializing in data engineering and computer vision

Bellevue, WA1y exp

“Former Amazon intern who owned an end-to-end computer vision system to detect package anomalies in fulfillment centers, from data collection/labeling to production deployment on AWS (EC2/S3) with a Streamlit live-monitoring dashboard. Also has ML-in-production experience deploying and updating a recommendation model on Kubernetes (Minikube) with CI/CD via GitHub Actions, plus prior SDE experience with Jenkins-based pipelines and on-prem to AWS migration work using Glue.”

Jingfei Xu

Screened

Intern/Junior Software Engineer specializing in AI/ML and cloud-based systems

Mountain View, CA0y exp

“Embedded/robotics software engineer with Hyundai Motors experience who owned an AI-driven perception validation pipeline using a Transformer-based approach to generate stable synthetic in-cabin audio for autonomy/ASR testing, cutting downstream testing time by 50%+. Has hands-on ROS integration (IMU sensor streaming, inference, control nodes), MQTT-based distributed messaging, and cloud/container deployment experience (Docker, Node/Express, AWS, CI/CD).”

Nishant Pathak

Screened

Executive Engineering Leader specializing in cloud-native platforms and security

14y exp

“Former CTO of EzCred, a fintech embedded finance/digital lending infrastructure startup that built an API-first underwriting and servicing platform using alternative data (e.g., GST and bank statements) to cut loan decisions from days to minutes. Helped raise $1M in seed funding, built the engineering org and compliance-ready cloud architecture, and ran partner pilots before the company shut down during COVID-driven lending market contraction.”

“Four-time founder with hands-on experience inside angel- and venture-backed executive teams, plus accelerator mentorship experience. Brings a practical, customer-validation-driven approach to company building, with strong insight into early-stage team dynamics and investor ecosystems.”