AI-native vs Legacy Fintech Engineering Teams

AI in FinTech has moved way beyond proof-of-concept. The companies pulling ahead aren't just experimenting with AI - they have someone leading it. Someone who connects business vision with technical delivery. Someone who makes AI embedded, not bolted on. That's what a Head of AI brings to a scaling FinTech. 📖 Deep dive into the responsibilities, team structures, and what makes this hire so critical: https://lnkd.in/eSrhtgKv #FinTech #HeadOfAI #AIStrategy #TechTalent

The role of Head of AI in FinTech isn't just a senior data hire - it's a strategic leadership position that sits at the crossroads of technology, product, and commercial growth. From owning the AI roadmap to embedding AI across the entire stack, this role is shaping the future of financial services from the inside out. We've broken down exactly what this role involves, what good looks like, and why your FinTech needs one now. 👇 Read the full insight: https://lnkd.in/eSrhtgKv #FinTech #HeadOfAI #AIStrategy #TechTalent

The conversation around AI in New York's fintech market has changed significantly over the past 12 months. It's no longer about exploring AI use cases. Businesses are now focused on building production-ready AI platforms that deliver real commercial value, whether that's automating regulatory processes, enhancing fraud detection, improving customer experiences or enabling internal teams with AI agents. As a result, we're seeing increasing demand for AI Engineers who combine strong software engineering fundamentals with experience building and deploying LLM applications, RAG architectures and cloud-native AI solutions on Azure and AWS. One of the biggest challenges for hiring managers isn't identifying where AI can add value it's finding engineers who have already delivered these solutions in production. At Salt, we're supporting businesses at different stages of that journey. Some need to scale permanent AI teams through Salt X, while others require specialist contractors to accelerate delivery through Salt Fusion. Every organisation is different, so having flexibility in how you access talent has become increasingly important. I'm looking forward to spending more time speaking with the New York AI and fintech community, learning where the biggest challenges are, sharing market insights and connecting with businesses building the next generation of AI products, as well as the engineers helping bring them to life. #AI #ArtificialIntelligence #FinTech #NewYork #AIEngineering #GenerativeAI #LLM #Cloud #Azure #AWS #Data #MachineLearning #Hiring #Recruitment

The hardest hire in AI right now isn't an ML researcher. It's the engineer who can take an AI agent out of the demo and make it survive contact with a real customer's messy, regulated workflow. That's the founding Forward Deployed Engineer seat at a YC-backed AI startup in insurance claims. What it actually involves: ➖ Putting AI agents into live claims operations for top insurance carriers ➖ Owning the technical customer relationship end to end: POV pilots, success criteria, turning prospects into paid contracts ➖ Founding-level equity and genuine ground-floor ownership On-site NYC. Fast process - 3 stages, no take-home. Most roles with "FDE" in the title put you third in line behind a PM and an AE. This one doesn't. You own the ambiguity and the outcome. Honest question for the engineers who've done this: what's the hardest part of getting an AI agent to hold up in real production - the integration, the edge cases, or the customer? And if you've lived that and want a founding seat, DM me - I'll send the brief. #ForwardDeployedEngineer

🚨 The best AI engineers aren't always choosing the highest offer. A trend I'm seeing in the market: Senior AI engineers are increasingly evaluating opportunities based on: → Technical autonomy → The quality of the engineering team around them → The scale and complexity of the problems they'll solve → The level of ownership they'll have Companies offering £20k more aren't always winning if the role feels like a step backwards in influence. For scaling Fintechs and SaaS companies, attracting exceptional AI talent is no longer just about compensation. Those days have passed. It's about answering: "Why would a world-class engineer choose to build this with us?" That's the question the strongest candidates are currently asking. #AI #FinTech #TalentAcquisition #EngineeringLeadership

There are fewer than 10,000 people in the US currently holding a "Head of AI" or "Director of AI" title. And demand is only accelerating. FinTechs that move now get to shape their AI roadmap before it's dictated by market pressure. Those that wait? They'll be competing for the same tiny talent pool (at a premium.) Here's why the window to hire senior AI leadership is shrinking - and what happens if you don't act. 🔗https://lnkd.in/ewur4BXH #HeadOfAI #FinTech #AIHiring #TechLeadership

The biggest lie in recruiting: "We need someone with 5+ years of experience in [technology that's existed for2 years]." I sourced for Agentic AI roles at Zoom. The framework (LangChain) is barely 3 years old. The concept of "agentic retrieval" didn't have a name until 2024. So how do you hire for roles where the required experience literally doesn't exist yet? You look for: • Adjacent expertise that transfers (distributed systems → agent orchestration) • Learning velocity over years of experience • Open-source contributions in emerging spaces • Research publications showing frontier thinking • Side projects that demonstrate curiosity The best AI hires I made weren't "experienced in agentic AI." They were brilliant engineers who could learn faster than the field was moving. Stop hiring for yesterday's requirements. Start hiring for tomorrow's problems. #HiringAdvice #AIRecruiting #AgenticAI #TalentStrategy #FutureOfWork #TechHiring

Not every business has someone triple-hatting as an AI expert, global operations lead, and de facto systems architect, all in one role. We do, so we sat down with Zen Foo, our Chief of Staff (Tech), to answer some of the questions we get asked most about scaling across borders. The real cost of expansion, whether AI can actually be trusted with compliance, and why fragmented systems are riskier than they look. Got a question on any topic, tech, AI, automation, or something else? Drop it in the comments. We've got experts across the team who can give you a real answer. Curious what it's like to think about these problems every day? We're #hiring: https://lnkd.in/g95vS3G5

AI did not just create new tools. It created a new kind of engineering role. My latest blog breaks down the rise of the Forward Deployed Engineer: the person who sits at the edge of product, customer workflow, AI systems, and revenue. It covers: - what FDEs actually do - why AI broke the generic SaaS deployment model - the technical stack behind the role: APIs, RAG, evals, agents, integrations - who this role is for - how engineers, PMs, consultants, and career-switchers can build toward it Read it if you are building with AI, hiring AI talent, or trying to understand why customer-facing engineers are becoming one of the highest-leverage roles in tech. The future of AI software will not be shipped from a roadmap alone. It will be deployed, debugged, and adapted in the field: https://lnkd.in/gccdjgiJ

AI is a defining moment. No doubt about that. The real question is different. Do you build the capability yourself, or do you trust it to external providers and consultants. For something this central, we believe you have to build it yourself. External partners can complement what you have. They can't replace it. Here's why. If an outside team spends a year and a half improving your software development process, you get a report at the end. You don't get smarter. The knowledge and the experience stayed with them, not with you. That only works if you go through it yourself. Try things, get it wrong, get it right, for two years, inside your own organization. That's why we're building actual AI engineering teams within FLEX, not adding an AI Analyst title to an existing role. It's not the only way to do it. But it is the way we believe in. #PrivateEquity #AI #Mittelstand #SoftwareMadeInGermany #BuildDontBuy