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Vetted Software Development Engineers in the Greater Boston
Pre-screened and vetted in the Greater Boston.
Piyush Dongre
Mid-level Full-Stack Engineer specializing in cloud-native microservices
“Backend engineer with hands-on experience scaling a CVE processing platform by re-architecting it into a Kafka-based distributed system, boosting throughput to 200k+ records/min while designing for HA, deduplication, and fault tolerance. Also led a Flyway-driven migration affecting 15M+ records with staged dev→stage→prod rollout, and has implemented production security patterns (Auth0, OAuth2/HTTPS, AWS IAM RBAC) including least-privilege hardening.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
Junior Full-Stack Software Engineer specializing in AI-powered SaaS platforms
Mid-Level Software Engineer specializing in cloud-native microservices for FinTech and Insurance
Mid-level Software Engineer specializing in cloud-native distributed systems
Senior Software Development Engineer specializing in full-stack and cloud applications
Mid-level Software Engineer specializing in AI agents and AWS cloud systems
Mid-level Full-Stack Software Engineer specializing in cloud systems and real-time platforms
Amit Prajapati
Mid-level Software Engineer specializing in full-stack development and applied AI
“Built a production RAG chatbot for Worcester Polytechnic Institute that indexes 500+ webpages using FAISS + Llama 3, with strong grounding/hallucination controls (confidence thresholds and citations). Also has internship experience orchestrating multi-step ETL pipelines with AWS Step Functions and delivered a 30x faster fraud/claims triage workflow at Munich Re using association rules and stakeholder-friendly dashboards.”
Sakshi Mohan Tapkir
Junior Software Engineer specializing in AI platforms and backend systems
“Built and shipped AI products at Humanitarians AI, including a full-stack multi-agent platform that consolidated six faculty AI tools into one interface and achieved 100+ user adoption, 70% less workflow switching, and a 6x latency improvement. Also designed a grounded document parser using FAISS and structured LLM outputs that reduced hallucinations by 60%, showing strong depth in both product-minded engineering and production AI systems.”