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Vetted CI/CD Professionals
Pre-screened and vetted.
Saniya Shinde
Mid-level Data Scientist specializing in NLP, LLMs, and RAG systems
“Built and deployed a production-style vision-language pipeline that generates structured medical reports from chest X-rays using BioViLT embeddings, an image-text alignment module, and BiGPT fine-tuned with LoRA, delivered via Streamlit and hosted on AWS EC2. Also collaborating experience presenting EDA findings, feature importance, and model performance to Ford managers while working with vehicle parts data at Bimcon.”
Yuvraj Singh Chauhan
Entry-level AI/ML Engineer specializing in LLMs, RAG, and DevOps automation
“Built and owned a production-scale AI-driven software release/version intelligence platform orchestrated via GitHub Actions that tracks 1000+ upstream repositories and automatically generates SLA-bound JIRA upgrade tickets for hardened container images. Replaced brittle regex/PEP440 parsing with an LLM-based semantic filtering layer plus deterministic validation to handle noisy/inconsistent GitHub tags at scale, with monitoring for coverage, latency, and correctness validated against upstream ground truth.”
Raviteja Kambhampati
Mid-level Full-Stack Java Developer specializing in cloud-native microservices and React
“Full-stack engineer who has owned customer-facing analytics and dashboard products end-to-end using TypeScript/React with Spring Boot microservices. Strong in scaling and stabilizing distributed systems (RabbitMQ, DLQs/retries, observability with correlation IDs) and in building internal tooling that consolidates ELK/CloudWatch signals to speed up support and operations; reported ~30% performance improvement on a recent dashboard.”
Sri Chandana Topuri
Mid-level Java Full-Stack Developer specializing in Spring microservices and Angular
“Backend-focused engineer working primarily with Python/Django who also handles full-stack responsibilities. Has hands-on experience deploying containerized Python/Java microservices to Kubernetes using Helm and GitOps (ArgoCD), plus building Kafka-based event streaming with reliability controls (acks, consumer groups, DLQ). Also supported major on-prem to cloud/hybrid migrations using Terraform/Ansible with blue-green cutovers and data replication to minimize downtime.”
Weston Carpenter
Mid-level Backend Software Engineer specializing in distributed systems
“Technical/presales engineer with experience at Grubhub and Appen, spanning LLM-adjacent data labeling workflows and production AI troubleshooting. Built an integrations platform at Grubhub and has hands-on experience diagnosing prompt-related AI failures via Splunk, adding JUnit tests and logging to prevent recurrence. Known for shipping customer-specific workflow adaptations (e.g., OCR annotation coordinate transformations for crop/rotation) while keeping timelines intact through iterative delivery and parallelization.”
Saicharitha Yanamandala
Mid-Level Software Developer specializing in Java, Cloud, and Microservices
“Backend/Python engineer who owned an end-to-end FastAPI + AWS internal natural-language document Q&A system (Textract extraction, embeddings/vector DB, LLM integration) with strong focus on reliability and latency. Hands-on with Kubernetes + GitOps (Argo CD, Helm, rolling updates/auto-rollback) and built/optimized Kafka streaming pipelines using Prometheus/Grafana. Also supported a zero-downtime on-prem to cloud migration with parallel run and gradual traffic cutover.”
Arthi R
Mid-level Full-Stack Software Engineer specializing in FinTech and cloud-native microservices
“Backend engineer with fintech/banking experience (e.g., Canara Bank) building secure Python/Flask microservices for financial reporting and unified data access. Strong in Postgres/SQLAlchemy performance optimization (including materialized views) and in productionizing ML services on AWS (Lambda/ECS/CloudWatch) with Docker, model registries, and blue-green deployments, plus multi-tenant isolation via JWT-based middleware.”
Shweta Gupta
Senior Backend Software Engineer specializing in Java microservices, Kafka, and AWS
“AI engineer who shipped a production chat assistant for a storage company by building the underlying RAG-style knowledge base (document ingestion, chunking/embeddings, FAISS vector store) and an admin update interface to keep content current. Also has full-stack delivery experience (Python REST APIs + React/TypeScript UI) and AWS operations using Terraform/Jenkins, including handling a real production performance incident by optimizing DB queries and adding auto-scaling.”
Ravi Bijinepalli
Senior ADAS/Autonomous Vehicle Validation Engineering Manager
“Controls and automated-vehicle engineer from the EcoCar EV Challenge who led an 8-person team implementing ACC and lane-centering directly on a vehicle (1st place result). Strong in CAN-based debugging, simulation-to-real deployment (Simulink to C++/dSPACE), and distributed robotics communication using DDS, with additional exposure to multi-agent RL and control barrier functions for coordinated driving.”
Kiran M
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and data platforms
“Backend/ML integration engineer with experience at Accenture and Walmart building Flask-based analytics and prediction APIs on PostgreSQL/MySQL. Strong focus on performance and scalability—uses precomputed aggregates, Redis caching, query tuning (indexes/partitioning/EXPLAIN), and async/background processing; also designs secure multi-tenant isolation with JWT and schema/db-per-tenant strategies.”
Shashank Nawathe
Senior Front-End Engineer specializing in React, micro frontends, and GraphQL
“Frontend engineer with Walmart Labs experience who contributed to the React Query (TanStack) open-source ecosystem by reproducing and helping fix a tricky cache invalidation edge case via a detailed GitHub issue and merged PR. Led measurable runtime performance improvements on a large B2B dashboard (D3.js), using memoization, component refactors, web workers, and virtualization to cut render time ~60% and eliminate UI freezes, and standardized data-fetching patterns to reduce data-related bugs ~30%.”
Shruthi Nandakumar
Mid-level Full-Stack Developer specializing in FinTech and cloud-native microservices
“Backend/AI engineer who owned a high-scale Java/Spring Boot microservice for a financial application (millions of requests/day) and led major reliability/performance fixes (including ORM/query and PostgreSQL tuning) achieving ~60% latency reduction. Also shipped application-layer LLM features for ops teams (summarization + tool-calling) with strong guardrails (PII redaction, validation, audit/feedback) and designed a state-driven agent workflow with retries, circuit breakers, and human escalation.”
Sanjay Mandru
Mid-Level Full-Stack Software Engineer specializing in cloud microservices and real-time analytics
“Software engineer who built a reusable React component package (UI modules, auth helpers, API client wrappers) for an AI SaaS background-removal project, emphasizing performance (tree shaking/dynamic imports) and reliability (Jest + Storybook). Also delivered a unified REST API for Samsung Big Data Portal, resolving cross-team issues by standardizing schemas, improving validation/logging, and operating effectively amid shifting requirements.”
Keerthi Kalluri
Senior Full-Stack & GenAI Engineer specializing in healthcare and financial services
“Built and deployed a production LLM-powered customer support assistant using a RAG backend in Python, focused on deflecting repetitive Tier-1 tickets and reducing resolution time. Demonstrates strong production engineering instincts around reliability (confidence scoring + human fallback), scalability/cost optimization (multi-stage pipelines), and workflow orchestration/observability (LangChain, custom DAGs, structured logging, step metrics).”
Niharika Bhasin
Intern Full-Stack Software Engineer specializing in AWS serverless and real-time web apps
“New-grad/early-career engineer who led high-stakes modernization of a field-operations platform from Firebase to AWS using an incremental/dual-write strategy, achieving zero downtime and ~30–32% infra cost reduction while improving scalability. Also built and productionized an AI-native code assistant (LangChain + Pinecone RAG) with measurable online metrics and safety guardrails, and has experience working directly with CEO/CTO/CPO and embedded with customer teams to ship enterprise features quickly.”
Nikitha Margadi
Mid-level Data Engineer specializing in cloud lakehouse, streaming, and MLOps
“Data engineer at AT&T focused on large-scale telecom (5G/IoT) data platforms, owning end-to-end pipelines from Kafka/Azure ingestion through Databricks/Delta Lake transformations to serving analytics and ML. Has operated at very high volumes (~50+ TB/day) and delivered measurable performance gains (25–30% faster processing) plus improved reliability via Airflow monitoring, robust data quality checks, and resilient external data collection patterns (rate limiting, retries, dynamic schemas).”
Akhilesh Babu Tumati
Mid-level Full-Stack Software Engineer specializing in cloud-native and AI-integrated systems
“Built and deployed a Virginia Tech CS department blog/archive application using a MERN/Next.js stack and a fully serverless AWS architecture (Lambda, API Gateway, S3, CloudFront, Route 53), including CI/CD via the Serverless Framework. Implemented RBAC for student/faculty/admin users and added an article export feature backed by MongoDB.”
Karan Javali
Mid-Level Full-Stack Software Engineer specializing in FinTech and cloud-native web platforms
“Software engineer with experience at Goldman Sachs and Arizona State University’s Learning Engineering Institute, shipping production backend systems including a vendor equities invoice-generation service designed for extensibility across multiple vendors. Built Django REST + PostgreSQL backends with JWT auth and Pytest coverage, and delivered data-heavy, responsive Angular dashboards; also has exposure to AWS EC2 deployments and GitLab CI/CD automation.”
Nikhitha santhoshi Maroju
Mid-level Full-Stack Software Engineer specializing in Java/Spring microservices on AWS
“Built and shipped a production LLM-powered fraud investigation agent using RAG to generate transaction explanations and draft analyst reports. Emphasizes production robustness (fallbacks, strict structured outputs, async orchestration, monitoring/evals) and reports measurable impact: ~12% precision lift and ~80 high-priority alerts per week with reduced manual effort.”
Eric James
Senior Game Developer specializing in Unity, gameplay systems, and blockchain features
“Unity/C# gameplay engineer who has owned and shipped modular progression/rewards/inventory systems, including a separated blockchain integration layer that drove higher engagement while keeping performance stable at scale. Also implemented AI behaviors with Unity ML-Agents using a training/inference separation approach, and has hands-on experience debugging platform-specific state issues during console certification across multiple shipped platforms (mobile/console/PC/WebGL).”
Sai Kumar
Mid-Level .NET Developer specializing in microservices and cloud-native FinTech/Healthcare systems
“Backend engineer with healthcare and financial services experience (Humana, PNC) who owned production-grade, high-volume ingestion-to-API pipelines end-to-end in C#/.NET and SQL. Strong focus on data quality, handling out-of-order/partial upstream records, and improving reliability/observability via structured logging and telemetry, plus significant SQL performance tuning to reduce peak-load issues.”
Krishnamraju Penumatsa
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
“Data engineer currently at American Airlines who built and owned end-to-end flight operations and booking data pipelines (batch + real-time) using Azure Data Factory, Kafka, Spark/Databricks, Synapse, and Snowflake—processing hundreds of GBs/day. Strong focus on reliability and data quality (idempotency, checkpointing, retries, validation/alerts) and delivered near-real-time analytics powering Power BI dashboards; previously helped stand up an early-stage data platform at Sysco on AWS (Glue/S3/Redshift) with Airflow and Jenkins CI/CD.”
Vishal Kodakanchi
Director of AI Platforms & Architecture specializing in enterprise GenAI and AI Centers of Excellence
“Software industry veteran (20 years) pursuing entrepreneurship; currently building an MVP software product aimed at solving specific finance and accounting problems for nano, micro, and small enterprises. Plans to run a metrics-driven pilot to validate demand before refining the product and raising capital; leveraging Google for Startups and exploring AWS for Startups.”
Kevin Cleveland
Staff DevOps Engineer specializing in cloud platform and SRE
“Platform/infrastructure engineer with hands-on ownership of Kubernetes, Terraform, VMware, and hybrid on-prem/AWS environments. Stands out for combining deep platform build/upgrade experience with strong incident response and reliability practices, including a Terraform redesign at H&R Block that reduced provisioning time by 40% and hybrid networking improvements that hardened Direct Connect failover.”