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Vetted Software Engineers
Pre-screened and vetted.
Mohit Patel
Junior Software Engineer specializing in DevOps and trading systems
“Worked on a long-running, high-dependency production rollout in financial post-trade systems, delivering trade-booking functionality on post-trade feeds used by multiple downstream teams. Emphasizes cross-team/external-team coordination and extensive testing to avoid disruptions, with additional experience improving application reliability via VPN-based resiliency measures.”
Omkar Tulsidas Parab
Mid-Level Full-Stack Software Engineer specializing in web apps, data pipelines, and ML
“Software engineer who owned an Order Management System end-to-end at Reliance Jio, improving large-table performance via UI virtualization shipped behind feature flags and refined through direct ops-user observation. Also built an OCR automation tool at Piramal Realty using Python/Tesseract with validation and manual correction fallbacks, driving adoption by operations teams. Experienced integrating with Kafka-based microservices and improving observability using structured logging and correlation IDs.”
Saniya Athani
Junior Software Engineer specializing in cloud-native DevOps and GenAI
“Cloud-focused engineer with hands-on experience deploying production cloud-native REST APIs on AWS using Pulumi IaC, containerization, and CI/CD, with strong emphasis on secure credential management and operational monitoring via CloudWatch. Also has IoT troubleshooting experience across edge hardware constraints and networking (TLS handshake failures), plus Python-based configurable data-processing tools and customer-facing requirements translation.”
“Backend-focused intern who built and refactored the backend for an LLM-driven gifting mobile app using FastAPI, tackling high-latency LLM + product-API workflows. Implemented async worker-pool/queue processing with Redis caching plus retries/fallbacks, cutting end-to-end suggestion latency from ~4–5 seconds to ~1 second while improving reliability and rollout safety via staged migrations and testing.”
maheen Adeeb
Senior Machine Learning Engineer specializing in LLMs, speech AI, and RAG systems
“AI engineer with production experience building multilingual speech-to-speech translation pipelines (ASR + LLM) for enterprise/media, focused on reliability at scale. Has hands-on orchestration experience (including IBM Watson contexts) and emphasizes production evaluation/monitoring using a mix of traditional metrics and LLM-based evaluators to catch quality regressions while balancing latency and cost.”
Swetha Sai
Mid-Level Software Engineer specializing in cloud-native microservices and analytics platforms
“JavaScript engineer with a track record of diagnosing and fixing real performance issues end-to-end—profiled a charting library freeze on large datasets, rewrote layout logic to batch updates, added tests, and got the PR merged upstream. Also has experience stabilizing backend services in ambiguous, fast-moving projects by defining priorities, tightening API contracts, and owning delivery through deployment.”
Aniruth Ravula
Mid-level Full-Stack Java Developer specializing in Angular and Spring Boot microservices
“Full stack Java developer (5 years Java/Spring Boot) building a mortgage-focused rule engine platform used by business users and developers. Experienced scaling data-intensive microservices on AWS (RDS/S3/SQS) and optimizing high-volume rule processing with SQL tuning, caching (KIE container), and asynchronous task decoupling; also delivers modern UIs in Angular and React (Redux/Toolkit).”
Vamshi Korra
Mid-Level Full-Stack Software Engineer specializing in FinTech and cloud-native microservices
“Open-source React dashboard/visualization library maintainer focused on runtime performance and API clarity. Led a significant effort to eliminate severe render lag on large live-updating datasets through profiling-driven refactors (normalized state, memoized selectors) and locked improvements in with CI, linting, and documentation that reduced regressions and improved external contributor onboarding.”
Andrew Snow
Senior Software Engineer specializing in real-time XR simulation systems
“Unity/C# gameplay engineer with VR shipping experience at Academental on a Meta Quest dental simulation product (Teo), implementing SmartFox-based multiplayer with room-code sessions and resync/reconnect handling to maintain shared POV training. Also building a roguelike platform fighter from the ground up with an ECS-style, data-driven combat system where attacks dynamically change by weapon (directional attacks, hitboxes, knockback/combos).”
Ioannis Gregos-Mourginakis
Mid-Level Software Engineer specializing in blockchain, data pipelines, and functional programming
“Built an LLM-powered production agent that scraped X.com data to categorize and profile accounts, deployed in Docker with automatic relaunch for high uptime. Interview details were limited, but the candidate does have hands-on experience shipping an AI automation workflow.”
Nithin Aitha
Mid-level Software Engineer specializing in FinTech and ML backend systems
“Backend-leaning full-stack engineer who has shipped real-time, customer-facing dashboards and ticketing/payment features at Freshworks and Global Payments. Strong in Python API design (Django/Flask/FastAPI) and React/TypeScript UIs, with hands-on experience scaling PostgreSQL for high transaction volumes and operating services on AWS, including incident response and HIPAA-aligned security controls.”
Robert Kennedy
Senior AI/ML Engineer specializing in LLMs, generative AI, and applied research
“Research-heavy ML/AI candidate with a PhD/publications background who translated LLM evaluation and clinical summarization techniques into production at ModMed. They owned an end-to-end healthcare GenAI pipeline that cut clinician documentation time from ~22 minutes to ~7-8 minutes, reduced token costs by ~30%, and built an internal evaluation framework later adopted by multiple teams.”
kartikeya tiwari
Senior Software Engineer specializing in AI systems and platform engineering
“Backend/AI engineer with experience owning production systems in fintech and product startups, including a predictive scaling platform that cut AWS spend by 40% and an ambiguous social-intelligence feature that doubled MRR from $50K to $100K. Also building AI search and document-processing workflows, with reported 99.7% extraction accuracy and hands-on use of both classical forecasting and modern LLM stacks.”
“Software engineer currently building AI-powered backend systems for interview analysis, with end-to-end ownership of an LLM-based monitoring platform. Stands out for combining practical product delivery in an ambiguous early-stage environment with measurable impact: over 40% reduction in manual review effort and roughly 20% lower inference cost.”
Luke Greely
Mid-level Software Engineer specializing in banking technology and reporting
“Developer in the mortgage domain who owns regulated client-letter and reporting changes across front-end scripting, serverless testing environments, and SQL/reporting workflows. They stand out for improving release operations by introducing SOAP UI testing, which nearly doubled letter-update throughput even while serving as the only developer on these projects, and for quickly resolving production issues within 24 hours.”
Tyler Moon
Mid-level Software Engineer specializing in medical device and embedded systems
“Software engineer from Abbott with hands-on experience building internal medical device engineering tools in MFC/C++/C#, including a reusable Trim Converter that automated manual workflows. Strong in modular architecture, asynchronous device communication, and iterating with users to improve reliability and workflow fit, now targeting fullstack engineering roles despite limited React/TypeScript production experience.”
Vaibhav Monpara
Mid-Level Full-Stack/Backend Engineer specializing in AWS, APIs, and GenAI systems
“Backend engineer who built the core backend for Air Kitchens’ discovery/booking platform on AWS (Node + Python, DynamoDB, SQS/Lambda), optimizing for fast user-facing APIs and scalable async workflows. Introduced an AI matching service with a deterministic pre-filter + LLM ranking approach to balance latency vs quality, and has hands-on experience with production security (JWT/RBAC/RLS), CI/CD, and blue-green, staged migrations from Django to modular services.”
Sindhuja Thagirisa
Mid-level Software Engineer specializing in backend, cloud-native microservices, and LLM apps
“LLM/agentic systems practitioner who repeatedly takes customer-facing LLM prototypes into production by operationalizing prompts, hardening RAG pipelines, and adding monitoring/guardrails. Has hands-on experience debugging intermittent production failures under high traffic (vector store timeouts/empty retrieval) and implementing fail-safe behavior plus alerting. Also partners closely with sales in pilots/POCs, customizing demos with customer data and running side-by-side comparisons to drive adoption.”
Urmila Kongathalla
Mid-Level Full-Stack Java Engineer specializing in microservices and cloud platforms
“Frontend/platform-leaning engineer who owned a shared React component library (design-system style) adopted across multiple SPAs, with strong discipline around SemVer, deprecation strategy, and developer documentation. Also has backend/distributed-systems experience diagnosing and fixing a Kafka microservice race condition and has led prioritization/migration planning in an unstructured monolith-to-microservices environment (Centene).”
Rishika Namineni
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices
“Full-stack engineer who owned end-to-end delivery of a customer-facing financial services web platform and built internal tooling for engineering teams. Strong in microservices and event-driven systems (Kafka/RabbitMQ), distributed transaction management (saga), and production performance/observability—achieving ~40% backend response-time improvement through database and query optimization.”
Tejaswini P
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and MLOps
“Built and deployed an LLM-powered financial/regulatory document analysis platform at State Street, combining fine-tuned transformer models with a RAG pipeline over internal knowledge bases. Owned the productionization stack (FastAPI, Docker, SageMaker, Terraform, CI/CD) plus monitoring for drift/latency/hallucinations, delivering ~40% faster analyst review and improved reliability through chunking/embeddings and grounding.”
Palaniappan Yeagappan
Junior Robotics Engineer specializing in autonomous driving and SLAM
“Robotics software engineer focused on real-time state estimation and perception pipelines, with hands-on C++/ROS work improving LiDAR+IMU odometry stability via an iterative EKF and careful timing/synchronization fixes. Has integrated LIO-SAM, built multi-robot communication bridges (ROS + custom UDP with heartbeat/fallback), and uses Gazebo + Docker for repeatable testing, backed by CI/CD experience maintaining Azure DevOps pipelines at Cognizant.”
Sourabrata Samanta
Intern Data Scientist specializing in AI, analytics, and cloud data engineering
“Built a production multimodal LLM-based vendor risk assessment platform that ingests SOC reports and other documents, uses a strict RAG pipeline with grounded evidence (page/paragraph citations), and dramatically reduces analyst review time. Experienced with LangGraph/LangChain/AutoGen for stateful, fault-tolerant agent workflows, and emphasizes reliability (schema validation, guardrails) plus low-latency delivery (~1–2s) through hybrid retrieval, reranking, caching, and model tiering.”