Vetted Jenkins Professionals

Sathvik Maridasana Nagaraj

Screened

Mid-level AI/ML & GenAI Engineer specializing in LLMs, RAG, and MLOps

5y exp

“LLM/agent engineer with production experience in healthcare claims automation, delivering large operational impact (cut case handling from ~8–10 minutes to ~3 minutes, ~2,000 staff hours saved/month at ~3,000 claims/month). Built resilient Azure-based deployments (Azure DevOps CI/CD, Docker/FastAPI, Redis caching, autoscaling, observability) and improved reliability via safety/evaluation frameworks that reduced hallucinations by 32%.”

Keerthana Kondabathini

Screened

Mid-level Full-Stack Java Developer specializing in Healthcare IT and FinTech

4y exp

“Backend engineer with hands-on experience in both financial services and healthcare, including a Capital One credit application platform and an AI-assisted medical-records-to-EMR pipeline. Stands out for owning systems end-to-end, improving response times by 30%, operating services at 50K+ daily requests, and applying strong validation/observability practices in regulated environments.”

“Backend engineer with strong payments and high-stakes transaction experience, including owning an Apple Pay/Google Pay integration via Stripe end-to-end in production for 100,000+ users. Particularly compelling for teams that need someone who can balance speed, security, and reliability in checkout or other sensitive backend workflows, and who has hands-on incident ownership in production.”

Vamsi Reddy

Screened

Mid-level AI/ML Engineer specializing in healthcare and financial ML systems

Nashville, TN5y exp

“ML/AI engineer with hands-on experience shipping both predictive healthcare models and clinical GenAI assistants into production. They combine strong MLOps depth across Azure and AWS with healthcare-specific safety thinking, including PHI guardrails, retrieval grounding, and production monitoring, and they also built internal Python tooling for fraud ML workflows at Capital One.”

“Currently at Berryble AI, this candidate is building an LLM-based real-time interview analysis engine using FastAPI, WebSockets, fine-tuned models, and GCP/Cloud Run. They stand out for using AI and agent workflows pragmatically to accelerate development while keeping human ownership over architecture, security, reliability, and maintainability, and they are also pursuing a master's in applied machine learning.”

Akhil Nakka

Screened

Mid-level Software Developer specializing in FinTech and cloud-native microservices

Remote, USA4y exp

“Full Stack Engineer in fintech (JPMorgan) who owns products end-to-end across React UIs and Spring Boot/Kafka backends, with a strong track record of shipping quickly while maintaining reliability via testing, monitoring, and feature flags. Has hands-on experience scaling microservices for high-volume transactions and debugging production latency using ELK/CloudWatch, plus built an internal Python/Flask automation tool adopted by backend engineers to speed API validation and debugging.”

“Built and shipped a production LLM feature that converts natural-language search requests into Lucene queries for OpenSearch-backed device event data, improving usability for non-technical users. Brings hands-on experience across the full stack of agentic systems: model training, FastAPI/React integration, Kubernetes deployment on AWS, event-driven orchestration with NATS/Kafka, and production-grade evaluation/observability.”

“AI engineer and current tech lead building a RAG-based multi-agent QA platform for financial document analysis at significant scale (40,000-50,000 documents). They combine Python, CrewAI, FastAPI, Hugging Face embeddings, Pinecone, and AWS SageMaker to deliver retrieval, calculation, summarization, forecasting, and visualization workflows, while leading a small cross-functional team.”

“Backend-focused engineer with strong .NET/Angular experience building enterprise financial and healthcare systems, including microservice APIs deployed with Docker/Kubernetes and AWS ECS. Demonstrates production reliability skills across secrets management (Secrets Manager/IAM), incident response (CloudWatch + Kafka failover), and data engineering patterns from SSIS ETL (data quality, incremental recovery), plus proven SQL tuning with a 10-minute report reduced to under 30 seconds.”

Vasudev Konde

Screened

Mid-level Full-Stack Java Developer specializing in APIs and cloud microservices

Phoenix, AZ5y exp

“AI/LLM engineer who has shipped a production document-intelligence agent that automated internal support workflows using RAG, tool calling, and robust fallback controls. Stands out for combining hands-on architecture with measurable business impact: 85% faster query resolution, 35% lower LLM cost, 40% fewer LLM calls, and enough automation to avoid adding 2-3 support engineers.”

“Banking infrastructure engineer who owns large-scale IBM Power/AIX (AIX 7.x, VIOS, HMC/vHMC) environments with hundreds of LPARs and deep PowerHA/SAN recovery experience. Also builds modern cloud delivery platforms—Azure DevOps/Jenkins CI/CD and Terraform for AWS/Azure (EKS/AKS, networking, security)—bridging legacy mission-critical systems and cloud-native automation.”

“CTO-for-equity founder who partners with non-technical co-founders to bring AI-powered product ideas to market, emphasizing financial viability and go-to-market planning over "just an MVP." Currently working with two other founders (CEO/Sales and CPO/industry expert) to launch a SaaS platform, leveraging AI coding tools (Cursor/Windsurf) for extremely fast, production-ready iteration with daily releases.”

Prashant Singh

Screened

Mid-level Backend/Platform Engineer specializing in data pipelines, reliability, and AI-assisted ingestion

8y exp

“Backend engineer who built and scaled a blockchain-based e-voting platform at early-stage startup Elemential Labs, balancing decentralization with real-world operability by centralizing control-plane components while keeping the ledger immutable. Has hands-on experience migrating high-throughput ingestion from Kafka to AWS Kinesis with parallel cutover, strengthening data integrity and read-after-write consistency (Elasticsearch), and hardening pipelines against silent data-quality failures via anomaly detection and self-healing automation.”

“Full-stack engineer focused on high-throughput document/financial data platforms, building Angular/React front ends and Spring Boot microservices with Python/Flask services for heavy processing. Experienced in designing non-blocking, asynchronous workflows (Celery/RabbitMQ) and deploying containerized systems to AWS ECS with auto-scaling and CloudWatch monitoring.”

Harshal Sawant

Screened

Senior AI Engineer specializing in LLMs, RAG, and MLOps on multi-cloud

8y exp

“Built and productionized a secure internal RAG-based AI assistant (LangChain/FastAPI/FAISS on GCP), tackling real-world issues like latency, retrieval speed, and hallucinations—delivering 25% faster retrieval and 99.9% uptime. Also implemented scalable, reliable ML retraining orchestration with AWS Step Functions/SageMaker/Lambda and partners closely with compliance analysts to iteratively refine prompts and outputs to meet governance standards.”

Kamal Virk

Screened

Senior Site Reliability Engineer specializing in cloud-native DevOps and Kubernetes

New City, NY13y exp

“IBM Power/AIX engineer with hands-on ownership of large AIX 7.1/7.2 environments (VIOS, HMC/vHMC) supporting enterprise middleware/back-end workloads. Demonstrated real production incident handling: identified CPU entitlement underprovisioning after a DLPAR change and restored performance via live CPU rebalancing, plus PowerHA failover execution and runbook/process hardening. Also builds secure CI/CD pipelines (Jenkins/GitLab/Azure DevOps with CyberArk) and Terraform IaC with drift management and controlled rollouts.”

“CTO/AI executive with repeated 0-to-1 leadership and founder experience across banking software, cloud, and fintech. Most recently, as a fractional CAIO, built a 50+ person team and launched 3 products in 9 months generating $10M+ new revenue; previously founded Trilogy (200+ clients in 7 countries) and created cloud tech that helped drive a $35M acquisition by VMware.”