Vetted Software Engineers

“QA professional with end-to-end ownership who combines automated, rule-based data validation (expected vs actual) with structured CAPA practices (5 Whys, Pareto, SOP updates, in-line checks, and hands-on training). Experienced coordinating multi-workstream QA timelines via centralized dashboards, weekly cadence, and escalations with third-party/global stakeholders.”

Mohammed Syed

Screened

Mid-level AI Engineer & Researcher specializing in healthcare AI and multimodal LLM systems

Remote2y exp

“Backend/ML engineer focused on clinical AI transparency who built ShifaMind, an explainability-enforced clinical ML system using UMLS/MIMIC-IV/PubMed data with RAG, GraphSAGE, and cross-attention. Demonstrated strong production engineering via FastAPI API design and safe migrations (feature flags/shadow inference), plus HIPAA-aligned auth/RLS patterns; also delivered a real-time comet detection system reaching 97.7% accuracy.”

Arpit Singh

Screened

Director-level Head of Technology specializing in e-commerce platforms and digital transformation

Dubai, UAE13y exp

“B2B product builder with prior experience taking products from 0-1 and scaling to revenue; previously implemented e-commerce search and turned it into a monetized paid-results/bidding platform requiring architectural changes and GTM alignment. Now exploring a startup idea focused on retention and upsell for B2B companies, targeting the underserved long-tail partner segment and already validating the gap with industry leaders and POC conversations.”

Jayanth Amol Ergola

Screened

Mid-Level Software Engineer specializing in full-stack development and data engineering

Milpitas, California4y exp

“Backend engineer with production experience at KeyBank building high-volume Java/Spring Boot services on Azure with PostgreSQL/Oracle, including async job ingestion and tracking. Demonstrates strong reliability/performance debugging (HikariCP pool exhaustion, DB contention) and has shipped an LLM-powered data analysis/summarization feature with robust production guardrails (validation, shadow testing, deterministic fallbacks, audit logs).”

Tanisha Dalwadi

Screened

Mid-Level Full-Stack Product Engineer specializing in TypeScript and React

Arizona, USA4y exp

“Software engineer and co-founder with 0-to-1 SaaS experience who built and owned an end-to-end reporting/analytics dashboard on Next.js App Router + TypeScript, including Postgres schema design, aggregation query optimization, and post-launch performance/monitoring. Has delivered measurable React dashboard performance gains (~35% improvement in time-to-insight) and built durable, idempotent job/state-machine workflows using serverless functions and Postgres.”

Anita Bhagashetti

Screened

Mid-Level Software Engineer specializing in distributed systems and cloud microservices

3y exp

“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.”

Arunim Samudra

Screened

Mid-Level Software Engineer specializing in LLM applications, RAG, and OCR automation

Austin, TX3y exp

“At Trellis, built and shipped a production multi-agent, authenticated GenAI chatbot for sensitive financial account inquiries (loan/payment lookups), using dynamic model routing to control latency and cost while improving accuracy. Implemented prompt-injection defenses (Meta Prompt Guard), RAG with LangChain, and LLM-as-a-judge evaluation; the system cut manual support call volume by 40%+ and was refined through close collaboration with QA-driven user testing.”

hetvi patel

Screened

Mid-level Software/Data Engineer specializing in cloud ETL pipelines and data infrastructure

New Jersey5y exp

“Backend/data engineer who built a production analytics data service (Python/FastAPI on AWS/Postgres with PySpark ETL) handling millions of records per day and drove major latency improvements (10–15s to <2s) via indexing, Redis caching, and shifting aggregations into ETL. Also shipped an LLM-based natural-language-to-SQL assistant end-to-end with strong guardrails (schema restrictions, read-only validation, RBAC, masking) and designed a multi-step agent workflow with verification and fallback logic.”

Joseph Whissel

Screened

Director-level Engineering Leader specializing in scalable SaaS, cloud, and embedded systems

12y exp

“Startup-experienced builder exploring an ambitious “internet 2.0” concept: a decentralized wireless mesh network using custom hardware nodes, with a security-first communications goal. Has thought through adoption mechanics via at-cost node distribution, usage-based crypto incentives, and an AR area-control game to drive network growth; also brings practical insight into what VCs value from working at startups including one owned by a PE firm.”

“Built and owned enterprise data/integration deployments and production AI workflows, including a Python-based migration pipeline that moved 2M records with major improvements in onboarding speed, error rate, latency, and uptime. Also shipped a financial RAG assistant over 50K documents with sub-second p95 latency, showing a strong blend of customer-facing deployment ownership, data engineering, and LLM systems expertise.”

“Full-stack developer building Lynx Cafe, a React Native/Expo iOS app for coffee shop customer feedback, while using AI and multi-agent workflows to accelerate scaffolding, architecture, and backend migration. Stands out for treating AI like a junior engineering team—assigning specialized tasks, manually integrating outputs, and enforcing code quality, security, and architectural consistency.”

“Built production LLM-powered mobile apps using OpenAI APIs on a serverless Firebase/Google Cloud Run stack, including a prayer app serving global users across five major religions with customized prayer generation. Stands out for adding reconciliation and scoring layers to validate non-deterministic AI outputs before showing them to users, and for iterating prompts based on logged failure patterns.”

Sanmith Kurian

Screened

Mid-level Software Engineer specializing in full-stack AI and FinTech systems

Remote, US4y exp

“Candidate applies a design-first approach to AI-assisted software development, using multi-agent setups across frontend, backend, and testing. They described building a multi-agent resume tailoring system and leading development of an AI-powered assessment interface for generating descriptive and MCQ questions, with architectural decisions including Redux for complex state handling.”

“Senior-level software engineer who uses AI pragmatically rather than blindly—leveraging Microsoft Copilot and LLMs for boilerplate, utility functions, and reusable React components while rigorously reviewing output for readability, reuse, and fit with project structure. Brings a strong maintainability mindset and prior experience reviewing code for junior engineers.”

“Graduate-level candidate who uses AI as a disciplined engineering assistant rather than an autonomous replacement, with hands-on experience coordinating manual multi-agent coding workflows across planning, implementation, and testing. They emphasize scoped execution, clear constraints, and human ownership of final merges, suggesting a thoughtful and practical approach to AI-augmented software development.”

“AI/LLM engineer with crypto/social-data domain experience who built an end-to-end AI trading signals and analysis backend using Next.js, Inngest, Gemini, and Supabase, including real-time progress UX and robust rate-limit/reliability handling. Also published an MCP SDK on NPM for authenticated agent tool access and built autonomous Twitter-based AI agents; strengthened reliability at LunarCrush by adding CI-gated E2E testing across web and mobile (Cypress/Maestro).”

“Built and showcased a self-made "Scholar AI" education web app that answers student queries and uses a RAG pipeline to ingest PDFs and generate MCQs for exam prep. Also delivered an AI solution for generating ad creatives and ad copy from keywords, emphasizing clear communication with non-technical stakeholders.”