Vetted Vector Databases Professionals

“AI engineer with experience taking a GPT-4-powered GenAI career coach toward production on Azure AI Foundry, re-architecting the backend with hybrid (vector + keyword) search and RAG optimizations to cut latency by 50%. Also has client-facing TCS experience building healthcare ETL pipelines and delivering error-free monthly reports, plus current work analyzing agentic system reasoning traces and guardrail drift as an AI research fellow.”

“Founding AI engineer at an AI SaaS startup who built the full GTM knowledge and retrieval stack for non-technical teams, driving 60% less manual effort and 25% faster deployments. Also brings enterprise B2B SaaS integration experience from Wipro, including external API/documentation work for large-scale partner ecosystems.”

“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”

Sudheer koki

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in predictive modeling, data pipelines, and RAG systems

Florida, USA5y exp

“Built and productionized an LLM-powered internal knowledge search system in a regulated environment, using embeddings/vector DB retrieval with strict grounding and confidence gating to reduce hallucinations. Reported ~45% accuracy improvement over keyword search and implemented end-to-end orchestration, monitoring, CI/CD, and incremental re-indexing to manage latency and data freshness while driving adoption with business stakeholders.”

“Built a production AI-native internal onboarding feature that reduced manual product setup effort by combining barcode API data, product photos, structured LLM outputs, and a polished real-time camera UI. Demonstrates hands-on experience across the full stack of LLM systems: prompt/schema design, multimodal inputs, backend orchestration with SQS and vector retrieval, and production reliability through evals, telemetry, and drift monitoring.”

Rathi Anand

Screened ReferencesStrong rec.

Senior Full-Stack Software Engineer specializing in Insurance, FinTech, and AI/ML applications

Dublin, CA17y exp

“AI/backend engineer who fine-tuned and deployed a production LLM chatbot using a LangChain + FAISS RAG pipeline, improving latency with PEFT/LoRA and driving strong business impact (40% customer adoption; 92% satisfaction). Also served as technical lead on a data aggregation system for underwriting/quoting, introducing GraphQL for more efficient, maintainable querying and applying CDC to keep cached ranking data fresh at scale.”

“ML/AI engineer with hands-on ownership of production recommendation and GenAI systems, spanning experimentation, deployment, monitoring, and iteration. Stands out for delivering measurable outcomes—22% CTR lift, 15% conversion lift, and a 30% reduction in support tickets—while demonstrating strong judgment on latency, cost, and safety tradeoffs in real-world systems.”

“Software engineer with 2 years of professional full-stack experience plus a CS master's journey in the US, who has since focused heavily on building hackathon-winning AI systems. Stands out for combining production-minded backend architecture, TypeScript-heavy reliability work, and multi-agent LLM applications spanning physical security and insurance claims automation.”

Shane Weinstock

Screened

Senior Data Scientist & Product Analytics Leader specializing in ML and experimentation

Austin, TX17y exp

“Aspiring founder with ~15 years of experience across varied backgrounds, motivated by frustration with slow, change-resistant large organizations and a desire to bring innovative ideas to market. Familiar with how venture capital/accelerators function (though not directly worked in them) and expresses strong willingness to take entrepreneurial risks.”

Sandeep Gandhi

Screened

Executive technology leader specializing in FinTech, identity, and AI-native platforms

San Ramon, CA26y exp

“Current CTO of Idmission leading a 150+ person engineering organization, with deep experience scaling delivery, CI/CD, and architecture modernization. Combines executive leadership with hands-on technical depth across microservices, Kubernetes, and AI systems, including a RAG support platform that reduced resolution time by 50% and passive liveness technology that improved client acquisition by 20%.”

“AI/LLM engineer with healthcare domain experience who built a production clinical support “chart bot” for Molina, including PHI-safe ingestion of 200k+ PDF policies, vector retrieval, and a fine-tuned LLaMA served via vLLM on ECS Fargate. Demonstrated measurable performance wins (HNSW + namespace partitioning; 30% inference latency reduction) and a rigorous evaluation/monitoring approach, while partnering closely with nurses and operations teams to shape workflows and guardrails.”

Job DelToro

Screened

Senior Full-Stack Engineer specializing in SaaS, cloud infrastructure, and video platforms

Guadalajara, México8y exp

“Full-stack engineer working at the intersection of product engineering and applied AI, with hands-on experience shipping real-time user features, MCP server integrations, and LLM-powered support systems. Stands out for combining TypeScript-heavy full-stack execution with production AI practices like retrieval architecture, confidence-based routing, observability, and evals, while driving measurable outcomes such as a 25% DAU lift and reduced support load.”