What's GTM Engineering: How to Scale Growth Without Hiring More

Let’s talk about scaling growth without the chaos. You’ve seen the flood of generic cold emails, right? The ones that scream “Hi [First Name], let’s hop on a call!” with zero context? That’s what happens when teams rely on manual grunt work instead of systems. Enter the GTM engineer—the architect behind scalable growth. They’re the ones connecting CRMs, automating outreach, and turning “spray-and-pray” into surgical targeting.

Here’s the reality: Companies using GTM engineering strategies see 2.3x faster pipeline growth than those stuck in manual outbound loops (source: Gartner’s 2023 Go-To-Market Automation Report). Tools like Clay empower GTM engineers to auto-generate hyper-personalized campaigns by stitching data from LinkedIn, Clearbit, and closed deals. No more interns copying/pasting into spreadsheets or sales reps drowning in busywork.

‍

Hold up—this isn’t just for Silicon Valley bros. Imagine you’re a SaaS company scaling from 100 to 1,000 customers. A GTM engineer would rig your CRM to auto-flag high-intent leads (like users who ignored your AI feature 10x), sync enrichment tools to personalize outreach, and A/B test subject lines at scale. Boom. Replies flood in while your sales team focuses on closing deals, not data entry.

‍

This is GTM engineering: where cold emails feel warm, pipelines self-fill, and your revenue engine runs like clockwork.

‍

What is GTM Engineering?

‍

GTM engineering is the technical discipline of building systems that operationalize growth by connecting product data, intent signals, and customer insights. It’s about designing workflows that find, prioritize, and engage your ideal customers at scale—without manual grunt work.

Here’s what it looks like in practice:

1. Defining and Targeting Your ICP:
   
   • Analyze historical wins to identify patterns (e.g., “80% of customers are Series B SaaS companies using AWS”).
   • Use tools like Clearbit and LinkedIn Sales Nav to scrape intent signals (job postings, funding news) that align with your ICP.
2. Automating Hyper-Personalized Outreach:
   
   • Merge product usage data (e.g., “User X ignored our AI feature”) with enrichment tools to auto-generate emails like:
     “Saw you’re scaling your DevOps team—here’s how we helped [Similar Company] cut cloud costs.”
   • Deploy sequences via platforms like Outreach or Salesloft, with dynamic follow-ups based on opens/clicks.
3. Self-Optimizing Campaigns:
   
   • Set rules to kill underperforming workflows (e.g., emails with <10% open rates after 48 hours).
   • Double down on what works, like A/B testing subject lines that reference a prospect’s tech stack or recent funding.

Tools like Clay are central to this process, enabling engineers to stitch CRM data, public intent signals, and personalized messaging into campaigns that feel human—not robotic.

The outcome? A self-replenishing pipeline that targets the right customers, eliminates wasted effort, and turns cold outreach into predictable revenue.

‍

LinkedIn’s 2023 Emerging Jobs Report found that demand for hybrid GTM/automation roles grew 217% year-over-year in SaaS (Source: LinkedIn). Why? Because blasting generic emails is so 2015. Today, it’s about systems that feel human at scale.

‍

GTM engineering open roles in the US

‍

How it blends product, marketing, and engineering

‍

Most companies treat product, marketing, and sales like separate kingdoms. Product builds the thing, marketing yells about the thing, and sales prays someone buys the thing. GTM engineering? It’s the translator that makes them actually work together.

‍

Here’s the raw, unvarnished truth:

‍

• Product teams track user behavior (e.g., "This customer used our AI tool 47 times last week").
• Marketing teams have buyer personas (but often guess who to target).
• Sales teams get handed "leads" that might as well be phonebook pages.

‍

GTM engineers bridge this by building systems like:

✅ Auto-tagging high-intent users in CRMs (e.g., "Flag anyone who used Feature X but didn’t convert")

✅ Syncing product analytics tools (Mixpanel, Amplitude) with email platforms (Outreach, Salesloft)

✅ Using Clay to cross-reference LinkedIn activity with company technographics for hyper-targeted messaging

‍

No vague stats. Just one example you can test yourself:

‍

1. Sign up for Clay’s free tier.
2. Build a workflow that scrapes LinkedIn for CTOs at startups using AWS (publicly available data).
3. Auto-generate emails referencing their recent posts about "cloud cost optimization."
4. Track open/reply rates vs. generic blasts.

‍

You’ll see why companies like Gorgias and Ramp use this stuff—it’s not theoretical.

‍

What GTM Engineers Do in Practice

Automating Outreach Workflows

Picture this: Your sales team spends hours copying LinkedIn bios into spreadsheets like it’s 2003. GTM engineers say ”nah, fam” and build robots to do it instead. How?

• Step 1: Scrape public job boards for companies hiring “Head of Cloud Cost Optimization” (translation: their AWS bill is on fire).
• Step 2: Use AI to draft emails that mention their exact pain (“Hey, saw you’re scaling DevOps – our tool saved Acme Corp 40% on cloud bills”).
• Step 3: Auto-send emails at 2:14 PM (when open rates peak) and auto-follow-up if they open but don’t reply.

The magic? It’s not the tools. It’s stitching data points (job posts + LinkedIn + emails) into a system that feels human, not bot-generated.

‍

Connecting CRMs, Enrichment Tools, and Outbound Platforms

GTM engineers are the ultimate tech stack DJs. They make Salesforce, HubSpot, and Outreach do the cha-cha slide together.

• Example:
  
  1. A lead visits your pricing page 5 times but doesn’t sign up.
  2. Your CRM (finally) notices and tags them as “hot lead.”
  3. A tool like Clay auto-pulls their LinkedIn to see they’re a CTO at a Series B startup.
  4. Outreach fires an email: “Congrats on the funding round! Here’s how we helped [Similar Startup] cut dev costs.”

No more “Hi [First Name]” hell. Just creepy-good relevance.

‍

Precision Targeting at Scale

GTM engineers prioritize accuracy over volume. Here’s how they systematically identify and engage high-intent leads:

1. Identify Pain Points:
   
   • Monitor public signals like LinkedIn job postings (e.g., “Cloud Cost Analyst”) or industry forums discussing specific challenges (e.g., “SaaS spend management”).
2. Enrich with Reliable Data:
   
   • Use B2B enrichment tools (Clearbit, Apollo.io) to match company domains with decision-maker emails and firmographics (e.g., tech stack, funding status).
3. Personalize Outreach:
   
   • Craft emails addressing specific pain points:
     Subject line: “Reducing AWS costs for [Industry] companies like [Theirs]”
     Body: “Noticed your team’s focus on cloud optimization – here’s how we helped [Similar Company] cut spend by 30%.”

This approach replaces generic outreach with relevance, using public data and compliant tools to align messaging with prospect needs.

‍

Build Systems and Pipelines Instead of Hiring More

GTM engineers don’t believe in hiring more interns to copy/paste. They build pipelines that:

• Auto-qualify leads (e.g., ghosted 3 demos? Move them to a “nurture” drip).
• Auto-kill campaigns that get <5% opens (no mercy).
• Auto-update CRMs when leads tweet about “budget cuts” (yes, really).

The goal? Replace human grunt work with systems that run while your team sleeps.

‍

The Fine Print

GTM engineering isn’t a silver bullet. It’s:

• Constant tweaking: What worked last month flops today. Stay paranoid.
• Ethics: Don’t scrape personal data. Target companies, not people.
• Tool fatigue: New SaaS tools pop up daily. Stick to 2-3 you actually master.

‍

TL;DR

GTM engineers are the mad scientists of growth. They mix product data, marketing chaos, and engineering rigor into systems that print pipeline. No hype, no jargon – just cold, hard automation.

‍

The Origins and Evolution of the GTM Engineer

GTM engineering emerged as companies prioritized scalable growth over manual efforts. When businesses shifted focus from “growth at any cost” to sustainable, efficient scaling, they needed roles that blended technical automation with sales and marketing operations.

This discipline combines CRM expertise, data integration, and workflow automation to solve core challenges: qualifying leads faster, personalizing outreach accurately, and maintaining clean pipelines. Instead of relying on large teams for repetitive tasks, companies now leverage GTM engineers to build systems that handle these processes at scale—freeing sales teams to focus on closing deals.

‍

ZIRP, Layoffs, and the Rise of Lean GTM Teams

Remember when startups had money falling out of their pockets? (Thanks, ZIRP-era free cash.) Companies hired growth teams like they were stocking up on toilet paper during a pandemic. Then 2022 hit. Interest rates spiked, layoffs went viral, and suddenly everyone had to do more with less.

Enter the GTM engineer. They’re what happens when you tell a growth hacker, “Cool tricks, but make it scalable,” and a sales ops person, “Drop the Excel and pick up an API key.” No more hiring 10 interns to manually scrape LinkedIn. Now, one engineer builds a system that does it for 10k leads while the CFO naps.

‍

From Growth Hackers to GTM Engineers

Growth hacking was the Wild West:

• 2014: “Let’s spam app store reviews!”
• 2018: “Viral loops! Referral codes! Free hoodies!”
• 2020: “Why is our CAC $900 and LTV $10?”

GTM engineering is growth hacking’s adult sibling. Instead of “hacks,” they build systems:

• Automating lead scoring, not just A/B testing subject lines.
• Connecting product usage data to sales plays, not just blasting cold emails.
• Fixing leaky pipelines instead of duct-taping them with freelancers.

The shift? Growth hackers chased quick wins. GTM engineers build highways, not dirt roads.

‍

SaaS-ification and Operationalizing Sales

Here’s the plot twist: SaaS turned sales into a factory. You can’t scale AC/DC concerts with a garage band. You need assembly lines.

• Old school: Sales reps manually hunting whales.
• New school: Systems that identify, qualify, and nurture leads before a rep even pings them.

Example: A SaaS company notices free users who export data twice are 5x more likely to convert. A GTM engineer rigs a workflow to:

1. Flag those users.
2. Auto-send a personalized demo offer.
3. Route hot leads to sales.

No more “Hey, wanna hop on a call?” into the void. Just math, code, and pipeline printing.

‍

Why GTM Engineering is Crucial for Cold Email

The End of Manual Prospecting

Let’s bury the cringe era of “Hi [First Name]” emails. You know the ones—where “personalization” meant swapping out the company name like a lazy Mad Lib. GTM engineers don’t just send emails; they weaponize data to make prospects think you’ve been stalking them (in a good way).

Imagine this: A founder tweets about scaling headaches → your system auto-sends an email with a case study titled “How [Their Competitor] Scaled Without Melting Down.” No human involved. Just code, caffeine, and chaos working for you.

‍

Personalization at Scale (Without the Cringe)

“Personalization” isn’t adding someone’s dog’s name to an email. It’s knowing their company’s tech stack, their latest funding round, and that they’ve been job-hunting for a “Head of Cloud Cost Optimization” (translation: their AWS bill is on fire).

GTM engineers build systems that:

• Scrape public data (LinkedIn posts, job boards, funding news).
• Auto-draft emails referencing exact pain points.
• A/B test subject lines like “Saw your DevOps hire 👀” vs. “Your cloud bill called. It’s crying.”

This isn’t magic. It’s just robots doing the creepy research you don’t have time for.

‍

Systems > Headcount: Building Repeatable Sales Engines

Hiring 20 SDRs to spam 100 emails a day is like using a flamethrower to light a candle. GTM engineers build systems that:

• Auto-qualify leads (e.g., “Only email CTOs at startups using AWS + Postgres”).
• Auto-nurture silent prospects (e.g., “They opened 5 emails but didn’t reply → send a breakup GIF”).
• Auto-kill campaigns that tank (RIP subject line: “Quick question…”).

The result? A pipeline that refills itself while your sales team actually talks to humans.

‍

GTM Engineers vs. Other Growth Roles

‍
Let’s clarify how these roles coexist and collaborate, rather than compete. Each has distinct objectives, but GTM engineers often act as the connective tissue between them.

GTM Engineer vs. Growth Marketer

• Growth Marketer: Focuses on generating demand through campaigns, ads, and top-of-funnel metrics (CTR, impressions, MQLs). They answer, “How do we attract more eyeballs?”
• GTM Engineer: Focuses on converting demand by automating lead routing, personalizing outreach, and ensuring MQLs turn into SQLs. They answer, “How do we turn eyeballs into buyers?”
  Synergy: Marketers bring leads; engineers ensure those leads get the right message at the right time.

‍

GTM Engineer vs. Growth Engineer

• Growth Engineer: Builds product-led growth features (e.g., referral programs, in-app prompts) to retain and expand existing users.
• GTM Engineer: Builds sales-led growth systems (e.g., CRM automations, enrichment pipelines) to acquire and nurture new customers.
  Synergy: Growth engineers optimize the product journey; GTM engineers optimize the sales journey.

‍

GTM Engineer vs. RevOps

• RevOps: Owns process and data governance—CRM hygiene, forecasting, and ensuring teams follow playbooks.
• GTM Engineer: Owns technical execution—building the tools, scripts, and automations that power those processes.
  Synergy: RevOps defines the roadmap; GTM engineers build the engine.

‍

GTM Engineer vs. Sales Enablement

• Sales Enablement: Equips reps with training, content, and playbooks to improve conversations.
• GTM Engineer: Equips reps with automated tools, lead insights, and workflows to improve efficiency.
  Synergy: Enablement teaches reps how to sell; engineers give reps better leads and less admin work.

GTM engineers don’t replace these roles—they amplify them. While others strategize, train, or govern, GTM engineers operationalize the vision with systems that scale. Think of them as the “how” to everyone else’s “what” and “why.”

‍

Anatomy of a GTM Engineer

Key Skills & Competencies

Think of a GTM engineer as a Swiss Army knife for revenue teams—they’re not experts at everything, but they’re dangerously good at stitching tools together. Here’s their toolkit:

• Low-Code/No-Code Automation: They turn clunky workflows into sleek robots using tools like Clay, Zapier, or Make. Imagine automating lead scoring so sales reps only see hot leads—no coding degree required.
• CRM Whispering: They make Salesforce, HubSpot, or Pipedrive sing by syncing them with product analytics, email platforms, and enrichment tools. (No, “CRM hygiene” isn’t just a buzzword—it’s their secret sauce.)
• Data Juggling: They don’t just read dashboards—they build them. SQL? Python? Basic fluency, but they’d rather use pre-built connectors than write novels in code.
• Campaign Architecture: They design sequences that feel human, like emails that trigger after a lead visits your pricing page twice. Creepy? Effective.

The GTM Mindset

Skills aside, GTM engineers think differently:

• Systems Thinking: They see pipelines like Lego sets—every piece (data, tools, teams) must snap together perfectly. If one block’s loose, the whole tower crumbles.
• Cross-Functional ADHD: They’re equally comfortable geeking out with engineers about APIs and explaining automation to a skeptical sales lead. (Yes, they’re the office translators.)
• Tinkerer’s Grit: They test, fail, and tweak. A workflow flops? They’ll rebuild it by lunch. Think of them as the MacGyvers of growth—always one paperclip away from a fix.

‍

Real-World Examples of GTM Engineering in Action

Case Study 1 – Awell Health (Healthcare Tech SaaS)

Problem:

• Struggled to break into the competitive U.S. market with a low-quality ABM list.
• Needed to target healthcare executives but lacked a clear strategy to identify decision-makers.

GTM Engineering Solution:

1. ICP Definition: Focused on healthcare executives (CMIOs, Clinical Ops Directors) at U.S. care providers.
2. Data Cleansing & Enrichment:
   
   • Used LinkedIn Sales Navigator + Apollo to validate and enrich leads.
   • Filtered out non-decision-makers (e.g., junior staff, non-U.S. entities).
3. Hyper-Personalized Outreach:
   
   • Created a 4-step email sequence addressing care pathway automation challenges.
   • Messaging tied to pain points: “Reducing clinical inefficiencies for [Hospital Name]-sized providers.”
4. Optimization: Adjusted messaging weekly based on open/reply rates.

Result:

• 20 demo calls booked in 2 months with U.S. healthcare decision-makers.
• 11 deals closed, including major care providers.

‍

Case Study 2 – Riskwell (B2B Risk Management SaaS)

Problem:

• Inconsistent lead quality and near-abandonment of cold email due to poor ROI.
• Needed to target high-intent companies in niche industries (civil engineering, transportation).

GTM Engineering Solution:

1. Intent-Based Targeting:
   
   • Used Bombora to identify companies actively searching for risk management solutions.
2. ICP Refinement:
   
   • Targeted CEOs, Project Managers, and Risk Officers in high-risk industries.
3. List Optimization:
   
   • Cleaned existing leads with Apollo + LinkedIn Sales Navigator.
4. Sequenced Outreach:
   
   • Emails focused on ROI improvements: “Cutting project overruns for [Industry] teams like yours.”
   • Follow-ups triggered by engagement (e.g., website visits).

Result:

• 42 demo calls booked in 4 months.
• 22 deals closed, including enterprise clients in construction and energy.

‍

Case Study 3 – Tatton Investment Management (Financial Services)

Problem:

• Complex service offering led to ineffective email campaigns.
• Outdated lead list and small TAM required precision targeting.

GTM Engineering Solution:

1. Messaging Simplification:
   
   • Broke down complex investment strategies into concise, benefit-driven emails.
   • Example: “Simplify portfolio management for your clients with low-cost, tailored solutions.”
2. Lead List Modernization:
   
   • Enriched lists with LinkedIn Sales Navigator to target financial advisors at UK-based firms.
3. Automated Follow-Ups:
   
   • Triggered personalized follow-ups after email opens/pricing page visits.

Result:

• 130 demo calls booked in 6 months.
• 52 deals closed, expanding Tatton’s footprint in financial advisory firms.

‍

Building a GTM Engineering Function

When to Hire a GTM Engineer

You don’t hire a firefighter when the house is already ash. Hire a GTM engineer when:

• Scaling Feels Painful: Your sales team drowns in manual tasks (copying data, sending templated emails).
• Silos Are Killing Growth: Marketing blames sales for bad leads, sales blames product for bad demos, and RevOps just sighs.
• You’re Ready to Scale Smart: You’ve nailed product-market fit and need systems to 10x pipeline, not headcount.

Real-World Trigger: A SaaS founder told me, “We hit $2M ARR and everything broke. Our ‘manual hustle’ model collapsed.” That’s when they hired their first GTM engineer.

‍

Team Structure & Reporting Lines

GTM engineers don’t fit neatly into org charts. They thrive in the chaos between teams. Common setups:

1. Under RevOps: Focus on CRM integrations, data pipelines, and sales tooling.
2. Under Growth/Marketing: Focus on lead gen automation, campaign personalization.
3. Under Engineering: Rare, but ideal if you need heavy API/custom tool builds.

The Sweet Spot: Embed them in a cross-functional “growth pod” with a sales lead, marketer, and product manager. They become the glue.

‍

Traits to Look For in Candidates

Forget “5 years of Salesforce admin experience.” Hire for:

1. Tool-Stack Fluency: Clay, Zapier, SQL, Python basics. They don’t need to code from scratch—just hack existing tools.
2. Systems ADHD: They see workflows as interconnected parts, not isolated tasks. Ask, “How would you connect LinkedIn scraping to personalized emails?”
3. Cross-Functional Charm: They’ll need to convince skeptical sales leads and jargon-averse marketers. Look for empathy, not ego.
4. Scrappy Experimentation: They should say, “I’ll try this workflow live right now” during the interview.

Red Flags: Candidates who obsess over “best practices” instead of shipping MVPs. GTM engineering is about iteration, not perfection.

‍

Challenges and Pitfalls

Automating Too Early or Over-Engineering

Ever tried to fix a leaky pipe with a flamethrower? That’s what happens when you automate broken processes. Startups often rush to “scale” before nailing their messaging or qualifying leads. Example: A company automated cold emails before defining their ideal customer profile (ICP). Result? Thousands of emails sent to the wrong people, tanking sender reputation.

How to avoid:

• Fix manual workflows first. If humans can’t do it well, robots will fail harder.
• Start small: Automate one high-impact task (e.g., lead enrichment) before scaling.

‍

Misalignment with Marketing/Product Teams

GTM engineers aren’t lone wolves. If marketing’s chasing crypto startups while product’s built for e-commerce, even the slickest automation will flop. Picture this:

• Marketing launches a webinar for SaaS founders.
• Product shares data showing their biggest users are e-commerce.
• GTM engineers build workflows for… neither, because priorities clash.

How to avoid:

• Weekly syncs with marketing, product, and sales. No exceptions.
• Shared KPIs (e.g., “Reduce lead-to-demo time by 50%”).

‍

Mistaking GTM Engineering for RevOps 2.0

RevOps ensures the car has gas and a map. GTM engineers build the car. Confusing the two leads to:

• Automating garbage processes (e.g., blasting unsegmented lists faster).
• Ignoring why systems break (e.g., bad data, not bad tools).

How to avoid:

• RevOps owns governance (what to measure).
• GTM engineers own execution (how to automate it).

‍

Future Trends in GTM Engineering

AI’s Growing Role in Outbound Systems

AI isn’t coming for your job—it’s coming for your manual workflows. Think of it as your co-pilot, not your replacement. Here’s how GTM engineers will wield AI:

• Hyper-Personalized Emails: Tools like Clay and Lavender already use AI to draft messages that mirror a prospect’s LinkedIn tone (e.g., casual vs. corporate).
• Predictive Lead Scoring: AI analyzes historical data to flag leads most likely to convert, like “CTOs at fintechs who tweeted about fraud detection.”
• Self-Healing Campaigns: If emails get marked as spam, AI tweaks subject lines or sending times automatically. No human panic required.

The catch: AI can’t replace empathy. The best GTM engineers will use it to enhance human intuition, not replace it.

‍

Rise of the Full-Stack GTM Engineer

Forget “coding vs. sales.” The future belongs to hybrids who speak both languages. A full-stack GTM engineer can:

• Build Custom APIs to connect niche tools (e.g., Shopify’s app store + Salesforce).
• Design No-Code Workflows for marketers to tweak campaigns on the fly.
• Translate Business Goals into technical specs (e.g., “We need 20% more SQLs → here’s the automation blueprint”).

Why it matters: Companies don’t want 10 specialists—they want one person who can bridge strategy and execution.

‍

Career Paths, Compensation, and Demand

GTM engineering is the Wild West of tech careers right now—high demand, low competition, and salaries that’ll make your coding friends jealous.

• Career Growth: Start as a GTM specialist → move into engineering → lead cross-functional ops teams.
• Compensation: Entry-level roles start at $90k–$120k. Senior engineers at scaling startups pull $150k–$200k+.
• Demand: LinkedIn job posts for “GTM engineer” grew 300% YoY (no, that’s not a typo).

The twist: As more tools democratize automation, the role will shift from “builder” to “architect”—strategizing systems, not just coding them.

‍

How to Become a GTM Engineer

So you wanna be a GTM engineer? Let’s cut through the noise. This isn’t about getting a fancy cert or memorizing Salesforce object models. It’s about becoming the person who fixes the dumpster fire everyone else ignores.

‍

Skills to Learn: Sales Ops, Coding, Systems Thinking

Forget “full-stack developer” vibes. You need a Frankenstein skillset:

• Sales Ops Basics: Know how pipelines should work (and why they’re always broken). Learn to spot dirty data like a hawk.
• Coding Lite: Python/SQL for simple scripts (e.g., cleaning CSV files, querying databases). No need to build apps—just hack existing tools.
• Systems Thinking: See workflows as LEGO sets. If marketing’s LEGO is purple and sales’ is red, you’re the weirdo who makes them snap together.

Example: A former SDR learned Python to automate lead scoring. Now he’s a GTM engineer making 2x his old salary. Not bad for a “non-technical” guy.

‍

Tools to Master: Clay, Zapier, CRMs

You don’t need to master every tool. Just the ones that make you look like a wizard:

• Clay: For stitching LinkedIn stalking + email automation.
• Zapier/Make: For connecting apps without crying over APIs.
• CRM Whispering: Salesforce, HubSpot—learn where the bodies are buried (e.g., custom fields, lead routing rules).
• SQL: To pull data without begging engineers.

Pro tip: Build a “Frankenstack” with 3 tools max. No one cares if you use 20 tools—they care if the right leads get emails.

‍

Building a Public Portfolio (No Coding Required)

GTM engineers are hired for proof, not resumes. Here’s how to show off:

1. Automate Your Own Job: If you’re in sales/marketing, automate your least favorite task (e.g., lead lists, follow-ups). Write about it on LinkedIn.
2. Break & Fix Public Workflows: Grab a free Clay template, break it, then rebuild it better. Screen record the chaos.
3. Share Case Studies: “How I 3x’d reply rates by scraping Reddit” > “5 Years of Salesforce Experience.”

Real example: A marketer landed a GTM role by automating her CEO’s cold emails. She documented every fail and win—chaos included.

‍

The Secret No One Talks About

You’ll suck at first. Your workflows will break. Sales will yell. But here’s the cheat code: iterate in public. Share your facepalms, fix them fast, and soon you’ll be the person companies fight to hire.