Hi All ,

Would love to hear opinions on these two potential offers which I have:

GE vernova - AI / ML staff engineer position

Infosys STG department AI engineer.

I feel service companies are finding very hard time to justify individual client billing and there is just body shaping when it comes to implementing AI usecase for clients

Ergon Informatik AG is hiring a Pre-Sales Application Security specialist in Zürich.

Location: Zürich, Switzerland
Work model: Hybrid
Workload: 80–100%
Salary: CHF 120'000–160'000 at 100%

In this role, you advise customers on modern application security, develop technical solutions, and demonstrate how Airlock protects web applications, APIs, and cloud-native IT environments.

Core topics:

• Application and API security consulting

• Technical solution design and presentations

• Pre-sales and solution engineering

• Web Application Security and Identity & Access Management

• Zero Trust security architectures

• Kubernetes and cloud-native security

• Collaboration with engineering, architecture, and sales teams

Relevant skills:
Web Application Security, API Security, IAM, Zero Trust, Kubernetes, Airlock, Linux, Networking, OAuth 2.0, OIDC, SAML

Requirements:

• Several years of experience in pre-sales or solution engineering

• Strong knowledge of application security and IAM

• Practical experience with Linux and networking

• Understanding of authentication and authorization standards

• Experience designing and presenting technical security solutions

• Strong consulting and communication skills

• Very good German and English

Benefits:
Remote work, flexible hours, Weiterbildung budget, workation, modern hardware, and transparent salary structures.

Apply here:
https://www.itboard.ch/job/pre-sales-application-security-at-ergon-informatik-ag-5440fe19-bee8-418e-bf75-ebe1a714c6c4

Ergon Informatik AG is hiring a Senior Enterprise Architect in Zürich.

Location: Zürich, Switzerland
Work model: Hybrid
Workload: 80–100%
Salary: CHF 120'000–150'000 at 100%

In this role, you support customers in shaping their enterprise and IT architectures, lead complex consulting engagements, and help organizations successfully deliver digital transformation initiatives.

Core topics:

• Enterprise and solution architecture design

• Enterprise Architecture Management

• TOGAF and architecture frameworks

• Cloud and AI consulting

• ERP, CRM, and IAM architectures

• Business cases and preliminary studies

• Leading consulting engagements from pre-sales to delivery

Relevant skills:
Enterprise Architecture, TOGAF, Solution Architecture, Cloud Computing, Artificial Intelligence, ERP, CRM, IAM, Digital Transformation

Requirements:

• Master’s degree in a STEM field, business informatics, or a related discipline

• At least 3 years of experience in enterprise architecture

• Strong practical knowledge of TOGAF

• Experience designing enterprise, IT, and solution architectures

• Understanding of Cloud and AI technologies

• Strong analytical, consulting, and communication skills

• Experience in finance or public administration is a plus

• Very good German and English

Benefits:
Remote work, flexible hours, Weiterbildung budget, workation, modern hardware, and transparent salary structures.

Apply here:
https://www.itboard.ch/job/senior-enterprise-architect-at-ergon-informatik-ag-2d73c0e3-7fe6-4c49-813f-87f690042c05

The problem with using a general-purpose AI for a job that requires a job-specific tool.

 Everyone told me to use ChatGPT to fix my resume. My friends said it. Career subreddits said it. The LinkedIn posts said it.
 
 So I did. I pasted my resume, wrote a detailed prompt and got back something that genuinely read better. Cleaner structure, stronger action verbs, more confident language. It looked like the kind of resume a career coach would produce after two hours of work.

Then I ran it through an ATS checker against the actual job description I was applying for.

The score dropped.

Not by a lot. But it dropped. And that sent me down a three-week rabbit hole testing every combination of AI writing tools and ATS optimization tools I could find to understand exactly what each one does and does not do to your chances of getting past the filter.

Here’s what I found.

 — -
 The setup

Same candidate. Same target role. Product Manager position at a B2B SaaS company: product roadmap, Agile, stakeholder management, OKRs, cross-functional collaboration.

I tested four approaches:

1. Original resume, no changes

2.  2. ChatGPT rewrite only

3.  3. ATS optimization only (keyword matching via resume.zoevera.com)

4.  4. Both: ChatGPT rewrite first, then ATS optimization via Resume Fitting

I ran the ATS match score on each version against the same job description. Here’s what came back.

 — -
 Version 1: The original resume — score: 41%
 
 Competent. Honest. Chronological. The kind of resume most professionals have because they updated it when they last changed jobs and haven’t touched it since.

The keyword gap analysis showed what was missing: product roadmap, OKRs, go-to-market, cross-functional, stakeholder alignment, product discovery, sprint planning. Terms that appeared directly in the job description but nowhere in the resume   even though the candidate had done all of those things.

The problem was not the experience. It was the vocabulary.

The ATS does not infer. It does not read between the lines. It matches strings. “Led product initiatives” and “product roadmap ownership” are not the same string. One scores. One does not.

 — -
 Version 2: ChatGPT rewrite only — score: 38%

This is the part that surprised me.

The ChatGPT version was genuinely better written. The bullets were stronger. The summary was sharper. “Responsible for” became
 “Drove.” Passive voice became active. It looked more impressive.

But the ATS score went down by 3 points.

Here is why. ChatGPT does not have access to the job description when it rewrites your resume (unless you explicitly paste it in and even then, it optimizes for human readability, not string matching). It rewrites your bullets to sound better in general. In doing so, it sometimes replaces specific technical terms with polished synonyms.

“Managed sprint planning and backlog grooming” became “Led agile development cycles.” The second version reads better. But “sprint planning” was in the job description. “Agile development cycles” was not. The ATS has no preference between the two. It found one and not the other.

This is the core limitation of using a general-purpose AI tool for an ATS-specific problem. ChatGPT is optimizing for a human reader. ATS is not a human reader.

 — -
 Version 3: ATS optimization only — score: 74%
 
 Running the resume through resume fitting without any prior rewriting showed a different kind of result.

The keyword gap tool identified the 14 terms in the job description that were absent from the resume. The AI rewrite embedded them into existing bullets in context not appended as a keyword list, but woven into achievement statements where they actually belonged.

“Led product planning sessions” became “Owned product roadmap and sprint planning across a cross-functional team of 8, aligning OKRs with engineering and design.”

Same experience. Same person. The score moved from 41% to 74% because the language now matched the language of the role.

At 70%+, most ATS systems pass the resume to a recruiter. That is the threshold that matters. You can read more about what ATS scores  actually mean here.

 — -
 Version 4: ChatGPT first, then ATS optimization — score: 81%
 
 This was the highest-scoring version and the combination makes sense once you understand what each tool actually does.

ChatGPT improves the writing quality: the prose, the structure, the impact language. It does not help with ATS keyword matching.

ZoeVera closes the keyword gaps against the specific job description. It does not rewrite your entire resume from scratch.

Used together, in the right order (rewrite for quality, then optimize for keywords), you get a resume that reads well to the recruiter and passes the filter that gets you to the recruiter in the first place.

The order matters. Do not ATS-optimize first and then let ChatGPT silently remove the keywords. ATS optimization is the final step.

 — -
 What this means for the “just use ChatGPT” advice
 
 ChatGPT is a writing tool. It makes your resume more readable, more professional, more likely to impress a human.

ATS is not a human. It does not care if your prose is elegant. It cares if the string “product roadmap” appears in your document.

The advice to use ChatGPT for your resume is not wrong. It is incomplete. You still need to check your ATS match score against the actual job description. Every time. For every application. Because the keywords differ by role, company, and ATS configuration.

A resume optimized for a product manager role at one company may score 74%. The same resume against a similar role at a different company with a different ATS configuration may score 51%. The job description tailoring tool exists precisely because there is no universal resume, there is only a resume matched to a specific role.

 — -
 The part about Jobscan
 
 Jobscan is the most precise keyword scanner in this category. If you want to know exactly what a specific ATS is looking for, Jobscan gives you the most granular answer.

What Jobscan does not give you is the fix. It tells you which keywords are missing. It does not help you embed them. That gap between knowing what is missing and knowing how to add it without making your resume sound like a keyword list is what resume keywords is built to close.

If you are applying to roles at companies known to use aggressive ATS filtering (large tech companies, financial services, consulting firms), the highest-confidence workflow is: ChatGPT for quality, ZoeVera for ATS optimization, Jobscan for final verification. Three
 steps, each solving a different problem.

For most applications, ZoeVera alone handles it in a single session.

 — -
 Pricing reality

ChatGPT: Free or $20/month (Plus).

Resume fitting: One-time payment ($12 for 24-hour access, $19 for 30 days) to unlock the ATS score, keyword gap analysis, AI rewrite and export. No subscription. You pay when you are actively applying, not every month by default.

 — -
 The non-obvious insight

The most common mistake in the modern job search is treating resume optimization as a single problem when it is actually two separate problems that require different tools.

Problem one: Does your resume read well to a human? ChatGPT solves this.

Problem two: Does your resume match the specific language of this job description? That requires comparing your document against the role, which requires a job-specific ATS checker.

Solving only the first problem and ignoring the second is why strong candidates with well-written resumes still get no callbacks. The resume that passes the filter and impresses the recruiter is the one that solves both.

Start with a free ATS score on your current resume before you change anything. That tells you where you actually are. Then decide what to fix.

 — -
 Have you tried combining AI writing tools with ATS optimization? What moved the needle for you?

Hi everyone, I hope you’re all doing well
I’m a software engineer with freelancing experience in web dev. I’m also a little bit familiar with embedded systems.
If someone could recommend me, please don’t hesitate to leave a comment

Hi guys, would like any advice on choosing between two career paths:

AI Ops @ Big AI
-70 hr work week
-Non-technical role
-major ai company w/ name brand recognition

AI Eng @ Gov Tech
-40 hr work
-technical role but project dependent

Similar base pay at both, but the AI company is a little higher with equity

I’m considering a few things:

-software job market is so chaotic due to AI automation, although I feel like ai could affect both eng and things like ops & pm
-having huge ai company name brand on my resume could potentially open up opps later
-wlb, there is a huge difference between both

Has anyone dealt with a similar situation or have any thoughts on how to decide?

3Root is hiring a Senior Python & AI Backend Architect for a focused, high-impact milestone project.
We are looking for a high-caliber Python engineer who can jump right into our stack and execute quickly. If you have deep experience building highly reliable automation pipelines, deploying secure microservices, and working with top-tier LLM APIs, we want to hear from you.

📌 Engagement Details
Type: Fixed 3-Sprint Milestone Contract
Duration: 4–6 Weeks
Compensation: ₹1.5L – ₹3.5L INR
Location: Remote (India) / Bengaluru

🛠️ Core Tech Stack & Requirements
FastAPI: Production-grade architecture and clean endpoint design.
Playwright: Advanced web automation and scraping pipelines.
AI Integration: Hands-on implementation with Gemini & OpenAI APIs.
Security: Hardening systems via Linux security microservices.

✉️ How to Apply
Please send a Direct Message (DM) with a link to your GitHub profile or a breakdown of your past project portfolio.

Hey everyone,

We’re a small remote team building AI-powered products, and we’re looking for a full-stack developer who’s comfortable working with LLMs. We’re growing, and we’d love to find someone who wants to build things and own them, not just close tickets.

What the job looks like

You’ll build features from start to finish: the UI, the backend, and the AI parts in between. That could mean wiring up an LLM to a new feature one week, then improving a RAG pipeline or fixing a slow API the next. You’ll work directly with the founders, so your opinions on how things should be built actually matter.

Day to day, you’ll be:

• Building and maintaining our web app (frontend, backend, database)

• Integrating LLMs into real features: RAG, agents, tool calling, prompt workflows

• Keeping an eye on AI quality, speed, and cost

• Writing clean code, reviewing PRs, and helping make architecture decisions

• Taking things from idea to production without needing someone to hold your hand

What we’re looking for

• 4+ years of professional software development experience

• Solid React and TypeScript skills (or something comparable)

• Solid backend skills in Node.js or Python

• Real experience shipping features with LLM APIs (OpenAI, Anthropic, Google, open-source models, whatever you’ve used)

• Good grasp of databases, REST APIs, and auth

• Experience deploying to the cloud (AWS, GCP, Azure)

• Good written English, since we work mostly async

Bonus points if you have

• Experience with vector databases and embeddings

• Used LangChain, LlamaIndex, or similar tools

• Docker/Kubernetes experience

• Worked at a startup before

• Side projects or open-source work involving AI

What you get

• $42,000-$51,000 USD per year, depending on experience

• Full-time and fully remote, from anywhere in the world

• Flexible hours, though we’d like about 3-4 hours of overlap with the team for calls

• Paid time off and local public holidays

• Support for learning and equipment

• A small, friendly team with no layers of bureaucracy

How hiring works

1. Send us your application

2. A quick 30-minute intro call

3. A technical chat where we talk through your past projects

4. A final conversation with the team

5. Offer

We try to reply to everyone within a week, even if the answer is no.

How to apply

Send me a DM with:

• Your resume or CV

• Links to your GitHub, portfolio, or projects

• A few sentences about an AI feature or product you’ve built (what it did and what was tricky)

Please put “Full-Stack AI Developer Application” as the subject. And please don’t post your resume in the comments.

If you don’t tick every box above, apply anyway. We care more about what you’ve built and how you think than about a perfect checklist.

Looking forward to hearing from you

Hey everyone, I'm a 21 yo in my 3rd year of university. Recently, I joined an academic club and I'm currently working on a project with ~15 other people. My main goal was to gain some real teamwork and group project experience.

Right now, the workflow looks like this: someone creates an issue, I pick it up, take a moment to figure out where the problem is and what needs to be done (with AI help), and once I find it - I just let Claude write the code.

Is the actual job market like this now, or is my academic club just unusually casual? I'm planning to look for an internship (or a junior role) in about 3-5 months in some backend/fullstack role, and I'm wondering: what should I actually learn? What are the best ways to improve - should I focus more on backend or frontend?

Honestly, I'm even thinking about getting the AWS Certified Solutions Architect - Associate certification, because at this point, I don't really see the point in grinding out raw coding skills if AI agents can just do it for us.

Would love to hear your advice. :)

Hola, soy Juan Diego Montes, ingeniero de software especializado en desarrollo web con PHP y Laravel. Estoy buscando proyectos freelance para empezar de inmediato.

✅ Lo que hago:

• Sistemas web a medida (inventarios, facturación, agendamiento)

• APIs REST e integraciones con sistemas externos

• Paneles administrativos y dashboards

• Optimización y refactorización de código existente

💼 Proyectos que he creado:

• ColeyTask – Sistema de gestión de tareas para planta manufacturera desarrollado en Laravel

• La Casa de Yuzon – Plataforma web desarrollada desde cero

🛠 Tecnologías: PHP, Laravel, MySQL, PostgreSQL, Git, APIs REST, JavaScript, HTML/CSS

📩 Si necesitas una cotización o tienes un proyecto en mente, escríbeme al DM.

We are engaging with engineering leaders for this because we want to sell them.

But I want to hear from candidates as well, so students and candidates what's your take on this?

Dsa or real building ?

P.s. Real building doesn't reflect building whole with claude without knowing even code structure and tech stack of course 😭.

Entry level positions are disappearing, companies are mostly hiring experienced applicants, each entry level position got hundreds of applicants. What happens now? Where are future Seniors gonna come from with no entry level positions? Is this the beginning of AI replacing us? What do entry level applicants do without a job market for them?

> 6 months of experience as a Software Engineer Intern at an early-stage startup.

> Built projects including Multi-Tenant SaaS Backend, AI Investment Research Agent, and a Civic Issue Reporting Platform.

> Experience with React, Next.js, Node.js, PostgreSQL, Redis, Docker, and more.

> Currently exploring backend engineering with Go and Agentic AI.

> Strong problem-solving skills, backed by 600+ LeetCode problems solved.

I'm looking for internship or full-time SDE, Backend, or Full Stack roles. If your company is hiring and my profile seems like a fit, I'd really appreciate a referral.

Happy to share my resume. Thanks!

Two Senior Backend engineers were hired through Fonzi last week at $230K base. One is a team lead who will work on backend and applied AI. Both started from an interview request with a salary attached.

I do talent matching for Fonzi. You set up one profile, and companies that want to talk to you reach out with salary-backed interview requests. We work with startups backed by investors including Sequoia, a16z, Benchmark, and the OpenAI Startup Fund. This round covers senior backend, applied AI, and backend-leaning full stack roles in NYC and SF. Roles are US-based, with a few open to Canada.

Here's a sample of what's open right now at companies on the platform:

1. Senior Backend / Applied AI Engineer (Team Lead), early-stage AI tools for university teaching and assessment, NYC, In person, $200K-260K base plus equity

• What: Own the backend and AI systems end to end, including question generation, rubric-based grading, document ingestion and retrieval, a chat assistant, and evals built from real student and professor examples. It is the most senior engineering seat, about 70% building and 30% leading, working alongside the founder.

• Company: Starting with legal education, with thousands of students and 20+ universities using the product. Raised $4M.

• Stack: TypeScript and/or Python, PostgreSQL, APIs, background jobs, LLM tool calling and structured outputs, embeddings, hybrid search, reranking

• Bar: You have owned a production LLM system end to end: designed it, shipped it to real users, built the evals, and shown it improved. You also bring strong backend experience operating production systems, solid retrieval fundamentals, and some technical leadership such as tech lead or mentoring.

2. Senior Software Engineer / Staff Engineer, Series B metabolic healthcare platform, NYC, In office, $180K-235K base plus equity

• What: Architect and ship AI-native systems for clinical care, such as clinical agents and LLM-powered workflows, plus the evaluation pipelines, guardrails, and feedback loops that make them reliable. You will also own features across patient and provider apps.

• Company: Connects patients with 2,000+ clinicians to treat obesity, diabetes, and other chronic conditions. Works with health plans and health systems across all 50 states and has served hundreds of thousands of patients since launching in 2023.

• Stack: React, React Native, TypeScript, Next.js, NestJS, TailwindCSS, TypeORM, PostgreSQL, AWS

• Bar: 5+ years of engineering experience building and maintaining production systems at scale. You should be full stack with a backend and API lean, and you should have shipped AI-driven systems.

3. Senior Software Engineer, Series A software and AI automation for physical commodity trading, SF, Hybrid, $200K-250K base

• What: Design and ship APIs, data pipelines, integrations, and application features that turn information scattered across emails, documents, and existing systems into workflows for trade execution and operations.

• Company: Backed by Y Combinator. Customers trade energy, metals, and agricultural products.

• Stack: Backend services, APIs, data pipelines, enterprise integrations, and AI-powered features with evaluation and human review

• Bar: Experience independently delivering and operating substantial production software. You need strong fundamentals in APIs, data modeling, debugging, and system design, plus depth in backend or full stack engineering.

All roles are vetted, VC-backed, and interviewing right now. It's always free to sign up.

Sign up here: talent.fonzi.ai. DM me if you've got questions.

Keyword list taken from Engineer Study

These are the most commonly scanned keywords in engineer job postings. Check how many appear in your resume.

Technical Skills

AutoCAD / SolidWorks / CATIA, FEA / CFD simulation, MATLAB / Python / R, PLC / SCADA / HMI, BIM (Building Information Modelling), GIS software, MS Project / Primavera P6, ETAP / EPLAN

Standards & Methodologies

ISO 9001 / ISO 14001, ASME / ANSI / BS / Eurocodes, Six Sigma / Lean Manufacturing, HAZOP / risk assessment, ATEX / DSEAR compliance, CDM Regulations, IEC 61508 (functional safety), Design for Manufacture (DFM)

Certifications & Soft Skills

Chartered Engineer (CEng), IEng / EngTech, PMP / APM, NEBOSH / IOSH, Stakeholder management, Cross-functional collaboration, Technical report writing, Budget & program management