Hi, I'm
Kevin Shah
Software Engineer | AI Engineer
I build and operate production LLM systems — agentic workflows, RAG pipelines, and multi-cloud AI platforms with systematic prompt evaluation, observability, and safety guardrails.
I take AI systems from prototype to production: LLM orchestration platforms, retrieval-augmented pipelines, prompt evaluation/optimization, and the observability and guardrails that keep them reliable at scale. Currently a Software Engineer on the Machine Learning Operations platform team at DNV; previously a Software Development Engineer at Amazon. Open to AI Engineer, MLOps, and Forward Deployed roles in the USA, Canada, Europe, and remote.
📍 Houston, TX — Open to USA, Canada, Europe & Remote
Experience
My professional journey building LLM systems, ML platforms, and backend services.
Software Engineer, Machine Learning Operations
CurrentDesign, build, and operate the AI platform behind agent-based products used across the business — retrieval pipelines, agent orchestration, evaluation, observability, and safety guardrails.
Grew through four phases in three years, partnering with product and engineering teams company-wide to turn use cases into shipped platform capability. Promoted March 2026.
AI Agent Platform
Apr 2026 – Present- ▸Productionizing an internal agent platform for organization-wide use — agent definition versioning, deployment and rollback workflows, and operational support for agents embedded in customer-facing products.
- ▸Built agent evaluation infrastructure: offline and regression harnesses, task- and step-level scoring, golden datasets, and automated quality gates that catch behavioral regressions before release.
- ▸Implemented end-to-end tracing and observability — span-level instrumentation of agent reasoning and tool calls, token and latency metrics, cost attribution, dashboards, and alerting.
- ▸Added a model gateway layer providing request routing, provider fallback, rate limiting, and cost attribution across multiple model providers.
- ▸Extended the platform with file handling, reusable agent skills, a sandboxed code interpreter, and standards-based tool integrations connecting agents to internal data sources.
- ▸Led the front-end architecture and UX redesign covering agent authoring, trace visualization, and evaluation review.
LLM Platform Engineering
Mar 2025 – Apr 2026- ▸Took ownership of a legacy LLM API service and re-architected it into a multi-provider platform serving teams across the organization.
- ▸Designed agentic workflow orchestration with persistent state, supporting multi-step reasoning and fault tolerance across long-running tasks.
- ▸Built retrieval-augmented generation pipelines end to end — document ingestion, chunking, embedding generation, vector indexing, and semantic retrieval.
- ▸Developed long-term agent memory services using top-k semantic retrieval to give agents durable, context-aware recall across sessions.
- ▸Built a prompt management system with LLM-assisted optimization and systematic evaluation — reduced hallucinations and cut a recurring 20-hour manual task to 3–4 hours.
- ▸Developed a knowledge-synthesis system that compiles cross-referenced documentation for model context injection, substantially reducing token usage and response latency versus full-context approaches.
- ▸Deployed inference-layer guardrails across environments via infrastructure-as-code — content safety, PII filtering, and hallucination mitigation.
Machine Learning Operations
Jul 2024 – Mar 2025- ▸Built a platform-agnostic ML workflow execution engine pairing managed training with lightweight container workers — sub-5s execution for non-ML steps and ~40% faster processing overall.
- ▸Developed ML training pipelines that generate evaluation metrics and publish trained models to an internal data lake for downstream inference, including anomaly detection.
- ▸Re-architected a legacy data-lake execution service into a serverless design, cutting infrastructure cost by ~50% and lowering operational overhead.
- ▸Built and scaled REST APIs connecting ML models to internal products, working with QA and product to resolve integration issues.
Full-Stack Application Development
May 2023 – Jul 2024- ▸Built a low-code website builder with custom drag-and-drop component blocks, letting users compose, style, preview, and publish pages from an internal component library.
- ▸Implemented page deployment pipelines on managed cloud infrastructure — CDN distribution, DNS, and infrastructure-as-code.
- ▸Designed and shipped a full-stack reporting tool that replaced a third-party product and eliminated its recurring license costs.
- ▸Extended reporting with SQL-based grouping, sorting, and filtering, and added functional test coverage for backend services.
Software Development Engineer
- ▸Contributed analysis and design for a promotion-code migration spanning 21 global marketplaces — part of a zero-downtime effort that preserved the experience for 550M+ customers.
- ▸Researched multiple legacy codebases behind a 10+ year-old global Order Summary system and designed a change to its shipping section, including A/B test planning, requirements gathering, and integration analysis across several Tier-1 services.
- ▸Built runtime customer-experience monitoring to detect aberrations, supporting global latency tracking and real-time impact measurement.
- ▸Completed on-call ramp-up in two months against a three-month norm; served two rotations, each requiring diagnosis of latency and customer-impact issues and ownership of the operations-review handoff for a 17-member global team.
- ▸Authored test cases, participated in code review, and remediated existing service code to improve maintainability.
Education
Master of Science in Computer Science
Bachelor in Computer Engineering
Skills
Technologies and tools I work with day-to-day.
MLOps / AI
Languages & Scripting
Backend & API
Cloud & DevOps
Databases
Frontend & Reliability
Get In Touch
Open to AI Engineer, MLOps, and Forward Deployed roles in the USA, Canada, Europe & remote.
Whether you have a role in mind, want to collaborate on a project, or just want to say hi — my inbox is always open. I'll do my best to get back to you promptly.
Email
kevinjshah2207 [at] gmail [dot] com
Location
Houston, TX · Open to USA, Canada, Europe & Remote
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