Vetted Audit Logging Professionals

premkumar narla

Screened

Mid-level AI/ML Engineer specializing in GenAI, RAG, and enterprise ML systems

Chicago, IL5y exp

“ML/AI engineer with hands-on experience at Morgan Stanley building production fraud detection and enterprise RAG systems. Stands out for owning systems end-to-end—from experimentation and deployment to monitoring and iteration—and for delivering measurable impact, including an 18% reduction in fraud false positives, 40% lower inference latency, and internal tooling that reduced model deployment time from days to hours.”

“Full-stack engineer with experience shipping analytics dashboards and an AI-driven support assistant for a cloud analytics platform. They combine Java/Spring Boot backend work with TypeScript frontend development and showed practical knowledge of LLM production concerns like retrieval grounding, latency, caching, retries, and graceful fallbacks. Their shipped dashboard feature improved load times by 35-40% and reduced support issues tied to delayed analytics.”

“JavaScript/TypeScript engineer with proven open-source impact: delivered a major reliability upgrade to a retry/error-handling library (standardized typed errors, added exponential backoff, expanded Jest tests, and implemented GitHub Actions CI) that was merged and released. Demonstrates strong performance engineering and debugging skills (profiling-driven optimization; diagnosed a race condition causing inconsistent retries) plus a documentation-first approach to developer experience.”

“Built and deployed a GPT-based RAG enterprise search system for healthcare clinicians, emphasizing low-latency performance and reduced hallucinations while maintaining end-to-end HIPAA compliance. Demonstrates deep applied experience with PHI-safe data governance (detection/redaction/de-identification), secure Azure ML deployment patterns, and orchestration of production LLM workflows using LangChain and Airflow.”

“Enterprise IT operations and identity governance professional (Atlassian) who partners closely with security teams to reduce risk through RBAC/Conditional Access automation, endpoint compliance, and vulnerability remediation workflows. Demonstrated ability to balance strict security controls with engineering productivity via phased rollouts, pilots, and KPI-driven stakeholder alignment, plus hands-on troubleshooting of complex Azure AD authentication failures and secure AWS integration design.”

“Backend/platform engineer who has owned end-to-end production systems in financial/claims domains, including a transaction analytics microservice platform processing ~10M daily operations and cutting latency from ~150ms to <70ms. Also productionized an LLM-powered monitoring/alerting capability (Llama 3 + FastAPI) with prompt design, guardrails, and production evaluation, and led monolith-to-microservices modernization on AWS using feature flags and parallel runs.”

Jaideep bommidi

Screened

Senior ML Engineer & Data Scientist specializing in LLM agents, retrieval/ranking, and MLOps

Denton, TX8y exp

“Machine Learning Engineer currently at Webster Bank building an enterprise-scale LLM agent for Temenos Journey Manager/Maestro, using RAG-style multi-stage retrieval with FAISS/Pinecone, hybrid dense+sparse search, and LoRA fine-tuning optimized via NDCG/MAP and A/B testing. Previously handled messy incident/telemetry data at Deuta Werke GmbH with deterministic + fuzzy entity resolution, and has strong production data engineering experience across Spark/Hadoop and Python ETL systems.”

“Engineering leader with 11 years at Nokia/Janus International scaling an engineering organization from 3 to roughly 50 people, plus recent startup experience building an AI-powered virtual property manager platform. Particularly compelling for roles needing a rare mix of hands-on architecture depth, people leadership, and cross-functional execution across backend, web, mobile, QA, and even hardware-integrated products.”

“Database/platform engineer with hands-on ownership of large-scale GCP data systems in financial services, including customer-facing SaaS investment products with strict SLAs. Stands out for leading an on-prem-to-GCP modernization using Spanner, AlloyDB, Bigtable, and BigQuery, and for building Terraform/Python automation that cut provisioning time by ~70% while improving reliability and self-service.”

“Backend/data engineer with production experience building secure Django/DRF APIs (JWT RS256 + rotating refresh tokens), background processing with Celery, and strong reliability practices (timeouts, retries/backoff, structured logging, audit trails). Has delivered AWS solutions spanning Lambda + ECS with IaC/CI-CD and built Glue/PySpark ETL pipelines with schema evolution and data-quality quarantine patterns; also modernized a legacy SAS pipeline to Python/PySpark with parallel-run parity validation and phased rollout.”

“LLM/ML platform engineer with hands-on experience taking an LLM document summarization prototype into a production-grade service on AWS EKS, emphasizing low-latency inference, drift monitoring, and safe CI/CD rollouts (canary + rollback). Strong in real-time debugging of agentic/RAG systems (tracing, retrieval/index drift fixes) and in developer enablement through practical workshops (Docker/Kubernetes/FastAPI) plus pre-sales support via demos and benchmarks to close pilots.”

“Full-stack engineer who built a policy management and notifications platform end-to-end: Java/Spring Boot microservices with PostgreSQL plus a React/Redux UI, deployed on AWS with Docker and Jenkins CI/CD. Demonstrates strong real-world scaling and reliability practices (Redis caching, Kafka, query/index tuning, ACID transactions, locking, and idempotent processing) to handle high-volume concurrent workloads.”

“Built and shipped LLM/RAG systems in finance and startup settings, including a Goldman Sachs document intelligence platform that indexed ~8TB of regulatory filings and delivered cited, conversational answers with <2s latency—cutting compliance research by ~4.5 hours per batch. Also developed LangChain-based agent workflows at Finta to automate CRM enrichment and investor lookup with strong testing, tracing (LangSmith), privacy guardrails, and auditability.”

“Backend/AI workflow engineer with experience at AirKitchenz, Uber, and Vivma Software, building production systems on AWS (Lambda, DynamoDB, Step Functions). Has a track record of major performance wins (DynamoDB latency 2s to <150ms; Postgres query 2s to ~180ms) and shipping LLM-powered onboarding and ticket-routing workflows with strong guardrails (schema validation, confidence thresholds, human-in-the-loop escalation).”

Utkarsh Chandel

Screened

Senior Security Engineer specializing in detection engineering, cloud security, and DFIR

San Francisco, CA8y exp

“LLM workflow/agentic systems practitioner who has helped customers harden an LLM-based incident triage prototype into a trusted daily-use production system by adding observability, audits, confidence gating, and deterministic fallbacks. Brings an SRE-style approach to real-time debugging (trace replay, rollback/canary, safe toggles) and is experienced running developer-centric demos/workshops and partnering with sales on technical qualification and security/architecture artifacts.”

Manasa Reddy Nagendla

Screened

Mid-level Full-Stack Java Engineer specializing in microservices, cloud, and event-driven systems

Cincinnati, OH6y exp

“Software engineer at Procter & Gamble focused on warehouse/operations systems, building near-real-time order/inventory visibility using Java/Spring Boot, React, Kafka, PostgreSQL, and Redis with measurable latency and load-time gains. Also shipped internal LLM/RAG knowledge assistants grounded in company runbooks and workflows, implementing guardrails and an evaluation loop that drove concrete retrieval improvements (document chunking) and regression prevention.”

Ramtin Kazemi

Screened

Junior Full-Stack Software Engineer specializing in Django, AWS, and AI/ML

San Diego, California1y exp

“Full-stack engineer who built and owned an AI-powered personal statement editor in Next.js (App Router + TypeScript), including dynamic routing, server-side data fetching, and typed API route handlers. Post-launch, they handled production monitoring/debugging and shipped reliability/performance upgrades (rate limiting, retries, rollback, DB indexing), and report a 40% latency reduction using Suspense/streaming and React concurrency patterns. Also implemented a durable Temporal-orchestrated AI document workflow with robust retry/idempotency strategies.”

“AI and platform engineer with 5 years of experience who built a production knowledge assistant for Verizon end-to-end, from architecture through deployment, monitoring, and incident hardening. Stands out for combining modern LLM/RAG systems with enterprise-grade rigor, including validation layers, observability, versioning safeguards, and measurable impact on technician productivity and retrieval quality.”

“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.”

“Java/Spring Boot engineer with startup-style ownership experience across e-commerce, banking, and healthcare analytics. Stands out for driving a monolith-to-microservices migration with Kafka that improved checkout reliability under peak load, while also contributing full-stack with Angular and supporting production operations end to end.”

“Software engineer with Citi Bank experience building real-time fraud validation/scoring for loan processing, spanning Spring Boot microservices and a FastAPI Python service secured with OAuth2/JWT. Delivered React/TypeScript operations dashboards and deployed containerized services via Docker/Kubernetes with Jenkins CI/CD, while also tuning databases (Oracle/Postgres) and handling high-volume latency/scaling issues using ELK, caching, and autoscaling on AWS.”

“Cloud/Kubernetes-focused production engineer with experience running 99.95% uptime platforms across AWS/Azure/GCP. Strong in incident response and performance troubleshooting (including a 30% MTTR reduction), and in building secure CI/CD and Terraform-based IaC for AKS/GKE microservices with robust change controls and rollback practices. Notably does not have direct IBM Power/AIX/VIOS/HMC or PowerHA/HACMP ownership.”

“Full-stack engineer who shipped a group scheduling SaaS feature with live availability updates using Next.js App Router + TypeScript, owning production reliability after launch (auth debugging, monitoring, polling/backoff tuning). Has hands-on experience with Postgres schema/index design and query optimization (EXPLAIN ANALYZE) and building durable orchestrated backend workflows with retries and idempotency.”