Vetted GitHub Actions Professionals

Mazhar Haq

Screened ReferencesStrong rec.

Senior AWS Cloud Architect and Technical Leader specializing in security, migrations, and cost governance

Santa Monica, CA26y exp

“Infrastructure/platform engineer with strong AWS and hybrid on-prem networking depth, spanning Kubernetes platform engineering (IaC, autoscaling, GitOps, observability) and large-scale VMware operations. Managed thousands of VMs across 56 US military bases/airports and has resolved real production hybrid incidents involving BGP/Direct Connect route advertisement and prefix-limit constraints.”

“Frontend-leaning full-stack engineer who described owning an artist search and detail experience across UI, backend integrations, and data modeling. They show practical strength in scalable React architecture, TypeScript safety, and performance tuning, with a product-minded approach to shipping 0→1 features quickly and iterating after launch.”

Manaswini Gogineni

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in cloud infrastructure and full-stack web development

San Francisco, CA2y exp

“Backend engineer at Electric Hydrogen who built a serverless device-log ingestion and processing platform in Python/Flask, scaling throughput (4x peak ingestion) while keeping sub-300ms API latency. Strong in Postgres/SQLAlchemy performance (partitioning, materialized views) and production ML integration (ONNX model served via FastAPI microservice with async batch inference, Redis feature caching, and drift monitoring via S3/Lambda). Experienced designing secure multi-tenant systems with schema-per-tenant isolation and KMS-backed encryption.”

“Backend/AI engineer who has built a rule-service platform on AWS and evolved it into an agentic RAG system using LangChain, ReAct, tool calling, and LLM-as-judge review. Notable for combining heavy AI-assisted development with production safeguards like manual CR, CloudWatch monitoring, fallback strategies, benchmark testing, and user-feedback-driven model improvement.”

“Machine learning/NLP practitioner at J.P. Morgan who led development of a production RAG system and an entity resolution pipeline for complex financial data. Deep hands-on experience with embeddings (Sentence-BERT), vector search (FAISS/pgvector), LLM fine-tuning (LoRA/PEFT), and rigorous evaluation (human-in-the-loop + A/B testing) backed by strong MLOps on AWS (Docker/Kubernetes, MLflow, Prometheus/Datadog).”

Nishitha Thummala

Screened

Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable inference

San Francisco, CA6y exp

“Backend/retrieval-focused engineer with production experience at Perplexity building a large-scale real-time Q&A system using retrieval-augmented generation, emphasizing low-latency, high-quality answers through ranking, context optimization, and caching. Also has orchestration experience from both product-facing LLM pipelines and large-scale infrastructure workflows at Meta, and has partnered with non-technical stakeholders to align AI trade-offs with business goals.”

Kowshika M

Screened

Mid-level AI/ML Engineer specializing in LLM fine-tuning, inference optimization, and AI safety

Santa Clara, CA5y exp

“AI/LLM engineer with production experience at NVIDIA, where they fine-tuned and deployed a financial-services chatbot and cut latency ~50% using TensorRT + NVIDIA Triton, scaling via Docker/Kubernetes. Also has consulting experience at Accenture delivering a predictive maintenance solution for a logistics network, bridging non-technical stakeholders with actionable dashboards.”

Sahil Sinha

Screened

Mid-Level Software Engineer specializing in full-stack development, cloud, and data infrastructure

Reston, VA3y exp

“Software engineer at Fannie Mae (~3 years) working on high-volume loan data pipelines using AWS (SQS/S3), Java listeners, Postgres, and Python/SQL-based data quality validation. Also built a chess data collection system (leveraging experience as an International Master) with robust retry/monitoring, schema-change handling, and idempotent backfills to prevent bad data from reaching downstream systems.”

Joseph Fusco

Screened

Senior Software Engineer specializing in AI-powered developer tooling and backend platforms

Marin, CA10y exp

“Backend/product engineer from Postman Flows who has owned complex platform features end-to-end, including production versioning and an LLM-powered flow-building orchestration layer. Stands out for combining product-minded backend design, agentic AI workflow implementation, and strong production reliability work, including re-architecting a failing event pipeline from in-memory to managed queues.”

Nikhil Reddy

Screened

Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms

San Francisco, CA5y exp

“Built and deployed an LLM-powered platform that turns models into scalable REST/gRPC APIs, focusing on keeping GPU-backed inference fast and stable during traffic spikes. Experienced with AWS orchestration (EKS/ECS/Step Functions), safe model rollouts, and production-grade monitoring/testing for reliable AI agents and workflows.”

Krishna Reddy

Screened

Mid-level AI/ML Engineer specializing in fraud detection and clinical LLM assistants

New York, NY6y exp

“Built and deployed a production clinical support LLM assistant at Mayo Clinic using a LangChain-orchestrated RAG architecture (Llama 2/PaLM) over de-identified clinical records, integrating BigQuery with Pinecone for semantic retrieval. Focused on healthcare-critical reliability by reducing hallucinations through grounding, implementing HIPAA-aligned privacy controls (Cloud DLP, VPC Service Controls), and running structured evaluations with clinician feedback.”

“Backend/full-stack engineer who has owned a production recruiting platform end-to-end (TypeScript/Node microservices for scraping/cleaning/serving job data, RabbitMQ for spike handling, MongoDB + Elasticsearch, AWS containers) with pragmatic CI, logging/alerts, and Docker Compose E2E tests. Also operated high-traffic event pipelines during a Binance internship using Kafka + Redis idempotency, with strong observability and failure-mode/rollback/degradation practices, and has experience designing developer-friendly REST APIs and resilient browser automation for E2E flows.”

“Recent internship project at Google Workspace building an LLM-driven Python backend pipeline to extract/enrich NLP features from messy customer web domains and integrate them into a Domain Feature Store for personalization and promotions. Also has hands-on Kubernetes/Docker deployment experience for a Digital Signage SaaS backend with GitHub Actions CI, plus strong streaming-systems knowledge (Kafka exactly-once, schema evolution, Flink scaling) and built an information retrieval system handling 30,000+ cases.”

“Fintech/neobank CTO (5+ years across US and UK markets) now building Payzo Money, a fintech copilot for SMBs covering expenses, accounting, invoicing, and payroll. Pre-revenue and seeking a $5M seed round, with active Bay Area conversations and a clear focus on bank sponsorship plus compliance/operations readiness; leverages Claude-based AI agents to accelerate building with limited resources.”

Kunj Amrutbhai Patel

Screened

Mid-level Software Engineer specializing in distributed backend systems on AWS

Seattle, WA4y exp

“Built production systems in the AWS ecosystem, including an internal AI assistant for diagnosing account transfer and permissions issues and an end-to-end account transfer workflow used by enterprise customers. Stands out for combining LLM/RAG design with strong distributed systems reliability practices, emphasizing guardrails, fallbacks, and operational trust in high-stakes workflows.”

“ML/NLP engineer focused on production-grade data and search/recommendation systems: built an end-to-end pipeline that connects unstructured customer feedback with product data using TF-IDF/BERT, Spark, and AWS (SageMaker/S3), orchestrated with Airflow and monitored for drift. Also has hands-on experience with entity resolution at scale and improving search relevance via BERT embeddings, FAISS vector search, and domain fine-tuning validated with precision@k and A/B testing.”

Ollie Jones

Screened

Executive Unity/XR Engineer specializing in real-time mocap and volumetric streaming

8y exp

“Technical Director/Unity Lead who has shipped multiple Meta Quest immersive experiences and built custom Unity editor tooling to solve content-heavy pipeline constraints, enabling artists to push content directly into a Unity sandbox. Also prototyped a Unity restaurant simulation where an LLM drives NPC reasoning and state machines, using RAG and memory augmentation to reduce hallucinations and stuck behaviors.”