Ask HN: Where to Work After 40?
Many software engineers hitting their 40s and 50s are questioning where their careers fit in an industry that often fetishizes youth, especially amid post‑2022 hiring slowdowns and fears about AI automation. Commenters describe a wide range of viable paths — from big tech, mid‑stage B2B companies, consulting, SRE and management roles to government, nonprofits, and niche domain work — and emphasize that networks, up‑to‑date skills, and willingness to adapt matter more than age alone. While some report bleak experiences with ageism and offshoring, others share success stories well into their 50s and 60s, arguing that experience, judgment, and work–life balance can become major advantages later in a tech career.
Overall job market after 40
- Experiences diverge sharply: some report offers and recruiter pings drying up around 2022; others in their 40s–60s say they’re still getting hired quickly into good roles.
- Several note that 2022 was broadly bad for hiring, not just for older workers.
- Some strongly pessimistic voices claim tech careers are effectively over after mid‑30s; many others call this exaggerated, citing their own late‑career moves.
Types of employers that work well
- Mid‑stage B2B software companies (100–500 people, C/D+ funded) are repeatedly praised: decent pay, real problems, less prestige pressure, good work–life balance, easier hiring bar.
- “Boring” enterprise consulting and professional services (including government contracting) are common landing spots, especially where seniority and communication matter.
- Non‑tech industries with large IT orgs (healthcare, finance, pharma, manufacturing, government) often expect and value middle‑aged staff.
- Nonprofits and local government are mentioned as lower‑pay but higher‑meaning, lower‑pressure options, sometimes with pensions.
Big tech / FAANG
- Mixed: some describe FAANG as a high‑pressure performance grinder with great pay; others say it’s relatively cozy and a good “retirement” gig after 40 with strong WLB.
- Getting in is seen as hard but not impossible; referrals and past tenure at big names help.
- Automated CV filters are debated: some think they’re overstated; others say mass applications feel like a lottery.
Consulting, contracting, and startups
- Consulting can work well for experienced people but brings stress around “billable hours” and bench time.
- Boutique consultancies and smaller firms are described as more humane than Big 4–style shops.
- Several over‑40s choose to start or join small startups, leveraging deep domain expertise, but worry about pigeonholing themselves as “startup people.”
Networking and community
- Strong emphasis on having an “F‑you network”: decades of colleagues, open‑source communities, mentoring relationships, and VC‑backed company networks that surface roles via referrals.
- Advice: even if you lack a big network, reach out to the contacts you do have.
Skills, specialization, and staying current
- Hiring managers note many older resumes show 20+ years on an unchanged legacy stack; this reads as stagnation and hurts employability.
- Others highlight older ICs who maintained modern skills (cloud, Rust, Typescript, AI, etc.) and are in demand.
- Deep specialization (“the X person”) can be powerful for small startups and niche industries.
Ageism, bias, and self‑presentation
- Some report direct age‑linked difficulties; others say age hasn’t mattered as long as they show current skills and reasonable salary expectations.
- Tactics: trim resumes to ~10–15 years, don’t foreground age, focus on impact and modern tools.
- Several warn that being a “career senior engineer” without progression in scope or role can become risky in later career.
Alternative paths and pivots
- Common pivots after 40–50: management, SRE/operations, QA/testing, technical writing, sales engineering, cybersecurity, academia/PhD, trades (e.g., electrician, handyman), indie game dev, small business.
- Government roles and some European contexts are highlighted as particularly age‑tolerant.
AI and automation
- Some fear AI will hit juniors harder; others worry about being made irrelevant or seeing demand shrink (e.g., technical writing with LLMs).
- A few treat AI as a tool to boost productivity while building “lifeboat” skills (e.g., learning a new language or domain).