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Vetted Jira Professionals
Pre-screened and vetted.
“Built an AI-driven insurance policy summarization platform at Marsh, taking it end-to-end from messy PDF ingestion/OCR and custom extraction through LLM fine-tuning and AWS SageMaker deployment. Delivered measurable impact (25% reduction in manual review time, 99% uptime) and demonstrated strong production MLOps/LLMOps practices with Airflow/Step Functions orchestration, rigorous evaluation (ROUGE + human review), and continuous monitoring for drift, latency, and hallucinations.”
SUMIT MAMTANI
Mid-level Data Scientist specializing in ML, MLOps, and customer analytics
“ML/NLP practitioner focused on insurance/claims analytics for a large financial firm, working with millions of fragmented structured and unstructured records. Built production-grade pipelines for entity extraction, entity resolution, and semantic search using Sentence-BERT + vector DB, including fine-tuning with contrastive learning (reported ~15% recall lift) and scalable ETL/containerized deployment on Kubernetes.”
Pravalika Kasojjala
Mid-level AI/ML Engineer specializing in LLM, RAG/GraphRAG, and fraud analytics
“LLM/agent engineer who has deployed a production internal assistant to reduce employee inquiry resolution time while maintaining regulatory compliance. Experienced with RAG, hallucination risk triage, and graph-based orchestration (LangGraph) for enterprise/banking-style workflows, emphasizing schema-validated, citation-backed, tool-constrained agent designs and tight collaboration with non-technical business/compliance stakeholders.”
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.”
Ashwini Ramesh Kumar
Junior AI Software Engineer specializing in LLMs, RAG, and agent workflows
“Backend/ML-leaning engineer who built a content-based event recommender for FlowMingle using embeddings + HNSW vector search on Google Cloud, with Firebase as the backend and a managed recommendation lifecycle (15 recs/user, daily async generation, weekly deletion) now serving 1500+ users. Also led a cost-driven migration of ConvAI services to Azure AI using parallel request testing from a Unity client, with post-migration monitoring via logs and model evals; contributed to a Massachusetts law-enforcement conversation analysis system by expanding ingestion to PDF/TXT/Excel and multi-file inputs.”
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.”
Melissa Floyd
Senior Lifecycle & CRM Marketer specializing in email/SMS automation and retention
“Lifecycle/CRM marketer from 5.11 Tactical who uses CDP-driven segmentation and rigorous testing to unlock incremental revenue and retention. Built post-purchase triggers that generated ~6,000 incremental repeat buyers and ~$1M in incremental revenue in a month, and proved the value of an underserved women’s segment (higher AOV/CTR) to secure increased investment and enable dynamic personalized email content.”
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.”
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.”
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.”
JL Pedat
Executive Marketing & AI Leader specializing in E-commerce, MarTech, and GTM strategy
“Founder building an AI-driven predictive analytics and programmatic advertising platform focused on identifying and marketing "hidden gem" songs and books. Has demonstrated early traction with 1M+ streams, a growing revenue base, acquired catalogs, and an artist roster, while developing proprietary AI and a supporting data ecosystem.”
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.”
Lakshmi Nallani
Junior Data Analyst specializing in analytics, BI, and machine learning
“Analytics-focused candidate with experience owning end-to-end data projects across AI transcription, retail forecasting, and transportation revenue analytics. They combine strong SQL/Python pipeline skills with dashboarding and stakeholder alignment, citing measurable impact including 60% lower ETL latency, 18% better forecast accuracy, and 25% operational efficiency gains.”
Christopher Schmitt
Executive Technology Leader specializing in FinTech & SaaS platforms
“Startup-oriented technology leader with 13 years in early-stage environments, including serving as CTO through Series A and Series B fundraising. Has direct experience presenting to investors and a board of advisors, and is especially motivated by taking products from idea to first sale and scaling them into real businesses.”