Ask HN: Who wants to be hired? (September 2026)

Location: Lucknow, India

Remote: Yes

Willing to relocate: Yes (India, Europe, US)

Technologies: Python, C++, PyTorch, FastAPI, Docker, Playwright, LLM agents (ReAct, MCP, tool calling), RAG, QLoRA/PEFT, quantization, Redis, PostgreSQL, AWS

Résumé/CV: https://drive.google.com/file/d/1qUxHkYu8dx866aGJy4-GLejJui7...

Email: shrey7shrey@gmail.com

Recent CS grad. I build agent systems and the verification machinery that proves they actually worked — the second part is where most of my time goes.

KARMA (github.com/ShreySharma07/Multi-Agentic-CUDA-optimization): 5-agent pipeline where LLM agents read NVIDIA Nsight Compute traces and rewrite CUDA kernels from measured bottlenecks. 8.99x over PyTorch eager, 87.9% of theoretical peak memory bandwidth, on a 6GB consumer GPU. I got a 40x early on that turned out to be a kernel computing garbage very fast — the model was optimizing my metric, not the task. Most of the work after that was a verification harness it couldn't game: compile gate, 3-seed correctness vs PyTorch, determinism gate, interleaved benchmarking. 0% false positives across every number I report.

Repliq (github.com/ShreySharma07/salesforce-agent): autonomous computer/browser-use agent. One narrated screen recording in, self-verifying execution plan out then the agent performs the task in a secured docker environment. 20-step Salesforce workflow end to end. Dominant failure mode was steps reporting success while the record silently never saved — fixed with per-primitive postconditions checked against real application state instead of agent self-report. just connect it with your org give me the task recording and done you don't have to worry about the day to day redundant tasks.

Looking for AI/ML or backend engineering. Happy to go deep on either project.

Location: Seoul, South Korea (UTC+9) Remote: Yes Willing to relocate: Yes, from late February 2027 Technologies: TypeScript, Node.js, NestJS, PostgreSQL, Redis, Kafka, Docker, Kubernetes, AWS, Terraform, CI/CD Résumé/CV: on request Email: sparkj.yoon@gmail.com Code: https://github.com/sparkYJO1

Backend and infrastructure engineer, four years, the last two and a half as tech lead of a five person team. I took a questionnaire assessment product from nothing to production on my own: schema, NestJS services, the scoring engine, the AWS infrastructure in Terraform, and the CI/CD. I still own that Terraform, including every change since, not only the first apply.

I build through AI rather than with autocomplete. The problem I kept hitting was not model quality. Every engineer on the team fed the tools different context and got different answers, so I standardised the specification documents and code generators across the codebase until the output stopped depending on who asked.

I also put an LLM into another product for questionnaire intake and result translation. It runs in staging and has been demoed to the customer, so I would not call it shipped.

The Github is small backend libraries, each one measured rather than guessed at, if you would rather read code than a CV.

Looking for remote work with an overseas company, or relocation to Europe. Happy to talk about either.

Location: India

Remote: Yes (Worldwide)

Willing to relocate: No

Technologies: Angular, Java, Spring Boot, REST APIs, LLM Engineering, Microservices, TypeScript, JavaScript, React, Node.js, SQL, AWS (EC2, S3), Git, CI/CD, Playwright, JUnit, AI Agents, RAG, MCP, Power Platform

Resume:https://drive.google.com/file/d/1VS9YQ6Hvz3Pw62RSjwQa7fe-Imy...

GitHub: https://github.com/harshvardhan-vhatkar

LinkedIn: https://www.linkedin.com/in/harshvardhan-vhatkar/

Email: harshuvhatkar@gmail.com

Software Engineer with 3+ years of experience building frontend applications, backend services, automated testing pipelines, and AI-powered developer tools. At my current company, I've improved Angular applications, built Spring Boot microservices with 100% unit test coverage, automated Playwright regression testing (reducing execution time from 2 hours to 30 minutes), and developed an AI-powered MCP server that generates Playwright tests from natural language, reducing test authoring from 45 minutes to under 2 minutes per spec. I enjoy building products end-to-end rather than working on isolated tickets. Recently I've been focused on AI developer tooling, RAG pipelines, MCP servers, and LLM-powered automation alongside traditional backend development.

Some highlights:

• Spring Boot microservices and REST APIs • Angular, React, Next.js, Node.js • AI Agents, MCP, RAG pipelines, vector databases • Playwright automation and developer productivity tools • AWS, CI/CD, SQL

I'm looking for a remote backend, full-stack, or AI engineering role where I can own features, work closely with a product team, and build software that ships to users. Startups and product companies are especially interesting.

If you're looking for an engineer who enjoys solving problems, automating repetitive work, and shipping production-ready software, I'd love to talk.

[dead]