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

Willing to relocate: Only for the absolutely right opportunity.

Technologies: Python, TypeScript (Nest.js for API, React for mobile or web front), Ruby, AWS (Architect, DevOps, AI/ML), Terraform, Kubernetes, Docker, PostgreSQL, Cassandra, LLMs, Scikit-learn(all MPL, SNS, pd, Data Science stack), Solidity, FinTech/Blockchain. (I've worked professionally with too many to write here and not give the feeling of "wall of text".)

Résumé/CV: baqueiro.com/static/baqueiro2025.pdf

Email: (in my resume)

Compensation Expectation: $140k and $170k USD gross yearly

Hello Hacker News! I'm a CompSci PhD (AI Multi-Agent systems... doing Agents' research back in 2004, before they were cool haha) and a passionate technologist with a warm spot for building high-impact products and teams.

For over 20 years, I've loved being a hands-on leader in FinTech, building everything from scalable crypto trading desks and AI/ML systems for fraud detection, to migrating entire platforms from monoliths to robust, cloud-native microservices. I thrive on aligning engineering with business goals and tackling complex distributed systems challenges.

Zero-to-One Success: Built foundational tech/AI/ML at a Fintech, enabling the company's Series A. Executive & Scaling Experience: CTO of a crypto trading desk; Head of Engineering, Product or AI/ML at high-growth FinTechs.

I'm actively looking for a remote role. I am most comfortable as first/founding engineer, also have been head-of/cto whatever the name building startup's technology teams. Right now I am most interested in doing AI/LLM work, like really pushing the status quo of both the Engineering and AI/ML. (I would love to get into something like SSI).

Willing to relocate: Yes

Technologies:

> Languages, Frameworks, and Libraries: JavaScript, Express, Ruby, Sinatra, Python, Flask, SQL, jQuery, TypeScript, React

> Cloud: Digital Ocean Droplet, AWS (EC2, VPC, S3, CloudFormation, CDK), Heroku, Fly.io

> AI Engineering: LangChain, Claude, Hugging Face, Vector DBs, embedding, OpenAI API, RAG, chunking

> Other Technologies: Node.js, Git/Github, Docker, Linux/Bash, HTTP, Nginx, PostgreSQL, MongoDB

Resume: https://drive.google.com/file/d/1RAO1NzfIRqbFRx_4-Qih6vzV8UJ...

Email: jow13_122@yahoo.com

Profile: I am a full-stack software engineer with several years of experience in Ruby and JavaScript, as well as additional proficiency in Python, TypeScript, and React. Most recently, I have been an open-source contributor to Mozilla Firefox, after participating in the creation of Vispyr, an open-source observability tool designed to make continuous profiling more accessible to developers.

Services: Web development, Data engineering, Cloud sysadmin + DevOps, Software consulting, Tech leadership

About Me: I’m Karan Krishnani, an independent software consultant with over 18 years of experience in full-stack development, cloud architectures, and AI integrations. I’m currently looking for projects as a fractional embedded team member (up to 20 hours/week). My background includes building scalable solutions for industries like healthcare tech, government, and financial services.

What my last client had to say about my work:

“Karan is a reliable and results-oriented individual who consistently delivered high-quality work.”

Technologies: Languages: JavaScript/TypeScript, Java, Python, Swift, PHP Frontend: React/Redux, Next.js, Vue, Angular, TailwindCSS Backend: Node.js/Express, Django, Apollo GraphQL, Sequelize Cloud: AWS, Azure, GCP, Heroku, Netlify, Vercel, Supabase AI/ML: Hugging Face, Jupyter, DataBricks, Transformers.js, OpenAI Whisper & Assistants API, Vector Stores, Retrieval Augmented Generation (RAG) Observability: AppDynamics, Sentry, DataDog, Grafana Other Tools: Docker, Terraform, Figma, Git, SST

Recent Highlights: • Tuva Health – Architected and delivered the HIPAA-compliant foundation for Tuva’s HEDIS quality-measurement service, a cloud-native platform on AWS ECS Fargate processing millions of patient records across 80+ NCQA measures.

Projects: https://karankrishnani.com/projects Résumé/CV: https://karankrishnani.com/resume LinkedIn: https://linkedin.com/in/karan-krishnani Email: karan.krishnani@gmail.com

Remote: OK

Willing to relocate: No

Technologies:

  ** Full-stack web (Postgres, Express, React, Node), Cloud infrastructure (AWS, GCP, OCI)
  ** PyTorch, Apache Spark, Apache Airflow, Kafka, Apache Aerospike, Apache Flink
  ** Postgres, MongoDB, Redis/Dragonfly, Cassandra
  ** CephFS, GlusterFS, ZFS, scaling and geo-distributing filesystems, LTO/LTFS
  ** LLM Integrations: Claude, OpenAI, Gemini, Mistral, DeepSeek, routers
  ** LLM fine-tuning, RAG/CAG, LoRA, MCP, Agentic workflows, GenAI, deep integrations
  ** Cloud Automation: Terraform, AWS Systems Manager, OCI Terraform
  ** Scaling, Clustering, Optimizing heavy throughput systems

  ** SOC and ISO pre-audit reviews for startups in the Storage as a Service, Healthcare, and Finance spaces.
  **  AI Startup Focused on Legal Discovery Management. Exited via acquisition.

Email: craig.carl.ca@gmail.com

I am a Full-Stack Engineer with 10+ years of experience and a heavy lean into DevOps. I enjoy building applications end-to-end—from the front-end components down to the server infrastructure and deployment pipelines.

Currently, I am developing the Ethereum File System (EFS), an open-source project where I wear both hats:

As a Developer: I architected a decentralized application using EAS, Solidity, TypeScript and Web Components, solving complex state management issues in a resource constrained environment.

As an Ops Engineer: I help run the underlying Ethereum network, using Prometheus and Grafana for observability and practicing chaos engineering to ensure node reliability.

Previously, I spent a decade at Epic Systems working on enterprise healthcare software. My work there involved modernizing legacy web platforms (C#/.NET) and managing large-scale server integrations, ensuring federated code worked reliably across varied and rigid enterprise environments.

I’m looking for a role where I can be useful across the stack, whether that means shipping features, improving build tools, or stabilizing infrastructure.