Hire Marketing Automation Experts With U.S. Support

Hire Marketing Automation Developers at SoftDoes — vetted, senior engineers backed by a U.S. delivery team. Start with one, scale to a full team.

  • Senior Marketing Automation Engineers

    Only vetted developers with 5+ years of experience.

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    Receive the first matching profiles within one business day.

  • Delivery Team Included

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Hire remote Marketing Automation Developer

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No exact match for this specialty yet — here are related experts from our network.

Aditya P.
Available Now
Aditya P.Verified in SoftDoes
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Andrea M.
Available Now
Andrea M.Verified in SoftDoes
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrew V.
Available Now
Andrew V.Verified in SoftDoes
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Boris S.
Available Now
Boris S.Verified in SoftDoes
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Eugene M.
Available Now
Eugene M.Verified in SoftDoes
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Hripsime S.
Available Now
Hripsime S.Verified in SoftDoes
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Mario J.
Available Now
Mario J.Verified in SoftDoes
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Raphael O.
Available Now
Raphael O.Verified in SoftDoes
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Santiago G.
Available Now
Santiago G.Verified in SoftDoes
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Thierry M.
Available Now
Thierry M.Verified in SoftDoes
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thomas S.
Available Now
Thomas S.Verified in SoftDoes
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Tzechung K.
Available Now
Tzechung K.Verified in SoftDoes
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

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What our Marketing Automation Developers
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What we do for you

From sourcing and vetting to onboarding and ongoing support, we handle the entire process so you can focus on building products instead of managing hiring.

Sourcing and vettingAll our developers are fully vetted and tested for both soft and hard skills. No surprises.
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Eugene M.DevOps EngineerAWS / GCP / Terraform / Gitlab
AWS / GCP / Terraform / Gitlab
Rate$53 / hour
LanguagesEnglish
previously at

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Frequently Asked Questions

Everything you need to know about deploying, scaling, and securing your neural agents with SoftDoes. Can’t find an answer?

How quickly can SoftDoes deploy senior marketing automation experts?

In most cases we can present vetted candidates within days of a discovery call, because our specialists have already passed our evaluation before you ever see their profiles. Once you select someone, onboarding begins as soon as access to your automation platform and CRM is granted. The exact timeline depends on how specialized your stack is and whether you need a single specialist or a full delivery pod, but the goal is always the same: an expert working productively inside your instance within a couple of weeks rather than the months a traditional recruiting cycle usually demands from your leadership team.

What pricing models and rates should we expect when hiring dedicated marketing automation talent?

Pricing depends on seniority, platform depth, and engagement structure. Most clients choose a dedicated monthly model for a full time specialist or pod, which gives predictable cost and continuity. For defined work such as an instance audit, a platform migration, or a lead scoring rebuild, a scoped project engagement can make more sense. We share transparent rates during the discovery session once we understand your platforms, the volume of work, and how much oversight you need. Compared with the fully loaded cost of an in house hire, including recruiting fees, benefits, and turnover risk, dedicated talent is usually a more efficient path.

How is time zone overlap with North America handled for marketing automation teams?

Because SoftDoes focuses on clients across the US and Canada, we plan every engagement around meaningful working hour overlap with your team. Specialists align their schedules so they can join standups, campaign reviews, and sales and marketing alignment meetings in your time zone. That matters in marketing automation, where launch windows, deliverability incidents, and sync failures often need quick decisions with stakeholders. We agree on overlap hours, communication channels, and escalation paths during onboarding, so your team always knows when the specialist is available and how urgent issues are handled, whether that involves a broken workflow or a time sensitive campaign launch.

What does your technical vetting methodology look like for marketing automation expertise?

Our vetting mirrors the real job instead of testing trivia. Candidates complete a campaign build exercise based on a realistic brief that includes segmentation, lifecycle goals, and a CRM constraint. They walk our marketing operations leads through real nurture programs they built, explaining the scoring logic, branching decisions, and results. We also present a messy instance scenario with old workflows, broken lists, and duplicate fields to see how they prioritize cleanup. Finally, we assess deliverability knowledge, compliance awareness across CAN SPAM, CASL, and GDPR, and how clearly they communicate tradeoffs to nontechnical stakeholders such as sales leaders and finance teams.

Who owns the intellectual property produced by experts working on our marketing automation systems?

You do. Everything our specialists create for you, including workflows, program templates, scoring models, email assets, documentation, integration configurations, and reports, belongs to your company. Our agreements assign intellectual property rights to the client and include confidentiality obligations covering your data, contact lists, and business processes. Work is performed inside your own platform and CRM accounts, so assets never live in a vendor owned environment that could hold you hostage later. If the engagement ends, you keep full control of the instance and its documentation, and we support a clean handoff to your internal team or a new partner.

How flexible are your contracts if our marketing automation project scope or team size changes?

Flexibility is built into how we work. Marketing priorities shift with product launches, budget cycles, and pipeline goals, so our contracts let you scale the team up when you need a migration or a major rebuild and scale down once the instance is stable and running. You can also adjust the mix of skills, adding reporting or CRM depth as needs evolve. If a specialist is not the right fit, our replacement guarantee means we provide a new expert without restarting your search or absorbing extra cost. We agree on reasonable notice periods upfront so changes never create disruption for your team.

The Executive Guide to Hiring a Marketing Automation Expert

A bad marketing automation hire rarely fails loudly. It fails quietly, through nurture programs that never fire, lead scores nobody trusts, CRM syncs that duplicate records, and emails that slide into spam folders while your pipeline thins out. Every month the seat stays empty or filled by the wrong person, your sales team works stale leads and your budget funds campaigns that cannot be measured. The right senior operator changes that in weeks, not quarters. This playbook gives you a field tested strategy to define, vet, and integrate top tier marketing automation talent without gambling your revenue engine on a resume.

Why This Hire Moves Revenue, Not Just Emails

What Real Marketing Automation Mastery Looks Like Beyond Button Clicking

Knowing where the buttons live in HubSpot or Marketo is table stakes. Senior marketing automation talent is defined by business impact, system resilience, and the judgment to manage tradeoffs between speed, data quality, and compliance. Here is what that looks like day to day:

  • Owning the lead lifecycle end to end. They design lifecycle stages, lead scoring based on fit and behavior, and the handoff rules between marketing and sales, then defend those definitions in pipeline reviews. When sales complains about lead quality, they diagnose the model instead of shrugging and adding another form field.
  • Architecting the CRM integration. They treat the sync with Salesforce, HubSpot CRM, or Microsoft Dynamics as critical infrastructure. Field mapping, sync rules, duplicate management, and campaign attribution get documented, tested, and monitored, because they know this is exactly where most automation programs quietly break and corrupt reporting.
  • Protecting deliverability as a revenue asset. They configure SPF, DKIM, and DMARC authentication, enforce list hygiene, and watch sender reputation closely. They understand Gmail and Yahoo bulk sender requirements and know that a beautifully designed nurture program is worthless if it never reaches the inbox of a real buyer.
  • Building compliance into the architecture. They map consent capture, unsubscribe handling, and data retention to CAN SPAM in the US, CASL in Canada, and GDPR for European contacts. Compliance is a design input from the first form they build, not a cleanup project after legal raises an alarm.
  • Auditing and refactoring messy instances. They walk into years of abandoned workflows, broken smart lists, and duplicate fields without panic. They inventory what exists, retire what is dead, consolidate what overlaps, and stabilize the instance so new programs can launch on clean, trustworthy data rather than inherited chaos.
  • Connecting automation to pipeline. They build attribution and campaign influence reporting, funnel conversion dashboards, and pipeline contribution views in the platform or your BI tools. They run disciplined A B tests on subject lines, content, and send times, and they report outcomes in revenue terms your CFO accepts.

The Business Case Your CFO Will Actually Sign Off On

Deep mastery of marketing automation pays back through specific, defensible mechanisms rather than vague promises of efficiency:

  • Reduced operational debt. A senior operator consolidates redundant workflows, cleans duplicate records, and standardizes naming and field governance. That lowers the hidden tax every new campaign pays today, shortens troubleshooting time, and stops your team from building fragile workarounds on top of a broken foundation that eventually collapses.
  • Faster campaign launch cycles. With reusable program templates, clean segmentation, and reliable lifecycle logic, launching a new nurture track or event campaign becomes a predictable process instead of a fire drill. Your marketing team ships more experiments per quarter and learns faster what actually converts buyers.
  • Better return on platform spend. Most companies pay for marketing automation features they never use and contact tiers inflated by dead records. A skilled specialist prunes unengaged contacts, activates underused capabilities, and makes sure the license you already pay for delivers measurable pipeline instead of shelfware.
  • Reliable revenue reporting. When CRM sync, attribution, and lifecycle stages are trustworthy, leadership can finally answer which programs create pipeline. That accountability lets you reallocate budget with confidence, defend marketing investment in board conversations, and stop arguing with sales about whose numbers are correct.

Groundwork Before You Open the Search

Audit Your Marketing Stack Before You Audit Candidates

Most failed hires trace back to a fuzzy problem statement. Before you talk to a single candidate, get brutally specific about what is broken, who the hire will work with, and how you want to engage the talent.

Name the Bottleneck Your New Hire Must Fix First

Start with the systemic constraint, not the wish list. Is your CRM sync creating duplicates and broken attribution? Is lead scoring so outdated that sales ignores it? Are deliverability problems choking your nurture programs? Or is the instance simply a graveyard of legacy workflows nobody dares touch? Each problem calls for a different profile. If reporting is the real pain, pair this hire with a partner in business analytics consulting so dashboards and data models are built on solid ground. Write the bottleneck down in one sentence. That sentence becomes your evaluation anchor.

Decide Between a Solo Specialist and a Delivery Pod

Next, define the autonomy level. An embedded marketing automation specialist works best when you already have a marketing operations leader, a clear roadmap, and someone who can make prioritization calls. A dedicated delivery pod makes more sense when you need a migration, a full instance rebuild, or parallel workstreams across campaigns, CRM integration, and reporting. Be honest about your internal capacity to manage this work. A brilliant individual contributor with no air cover will drown in ticket requests and never fix the structural problems you actually hired them to solve.

Weigh In House Hiring Against Vetted Dedicated Talent

Finally, choose the engagement model. A traditional full time hire brings long recruiting cycles, salary negotiation, benefits overhead, and real risk if the person turns out to be a strong platform user but a weak architect. Vetted dedicated remote talent compresses that timeline and shifts the replacement risk to your partner. The right choice depends on how urgent the problem is, how stable the scope will be, and whether you need permanent headcount or proven execution capacity now. Many teams start dedicated, then convert once the operating model is stable.

Build a Requirement Profile That Filters for Outcomes

Generic job specs attract generic applicants. Replace yours with a profile built on four non negotiable components:

  • Core outcome and mission. State the business result in plain terms, such as rebuilding lead scoring so sales accepts marketing qualified leads, or stabilizing the Salesforce sync so attribution is trustworthy. Candidates who cannot connect their past work to a comparable outcome should not advance further in your process.
  • Technical stack ecosystem. List your actual platforms: HubSpot Marketing Hub, Marketo Engage, Account Engagement (formerly Pardot), Marketing Cloud Engagement, ActiveCampaign, Klaviyo, Braze, or Customer.io, plus your CRM and BI tools. Depth on your platform matters, but transferable architecture thinking matters more than memorized menu paths.
  • Decision making authority. Define what this person owns outright and what needs approval. Can they retire workflows, change lifecycle definitions, or adjust sync rules without a committee? Ambiguous authority produces cautious operators who document problems endlessly but never fix them, which is exactly the outcome you are paying to avoid.
  • System impact. Spell out which downstream teams depend on this work: sales development, revenue operations, finance reporting, customer success. A senior candidate should immediately ask how changes will be tested, communicated, and rolled back. That instinct for protecting shared systems separates operators from order takers every single time.
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Vetting and Integration Without the Guesswork

A Vetting Framework Built for Marketing Automation Reality

Resumes in this field are notoriously inflated. Platform certifications prove someone passed an exam, not that they rescued a broken instance. Your process must expose real production experience.

Where Senior Talent Actually Comes From

Traditional recruiters screen for keywords: HubSpot, Marketo, Pardot, lead scoring. They cannot tell whether a candidate designed a scoring model or merely updated one point value someone else chose. That gap fills your calendar with polished interviews and disappointing hires. Pre screened marketing operations networks flip the equation by verifying production experience before you ever see a profile. Candidates have already been evaluated on real programs, real integrations, and real cleanups. Tapping a vetted talent network means your leadership time goes to assessing fit and judgment, not filtering out keyword optimized applicants who have never owned a live instance.

An Evaluation Pipeline That Mirrors the Actual Job

Skip trivia about menu locations. Instead, run a campaign build exercise: give candidates a realistic brief with a target segment, a lifecycle goal, and a CRM constraint, then ask them to design the program, scoring logic, and handoff rule. Follow with a review of real nurture programs they built, asking why each branch exists and what they would change today. Add an instance audit scenario with duplicate fields and broken lists. Throughout, watch how they communicate under pressure and whether they can explain tradeoffs to sales and finance stakeholders clearly, without hiding behind platform jargon.

The First 90 Days: A Ramp Up Plan That Pays Back Early

Onboarding determines whether you see return in one quarter or three. Use clear milestones:

  • Days 1 to 30: Access and audit. Grant admin access to the automation platform, CRM, and reporting tools on day one. The specialist inventories workflows, lists, fields, and integrations, documents deliverability authentication status, and delivers a prioritized audit with quick wins, structural risks, and a recommended sequence agreed with marketing and sales leadership.
  • Days 31 to 60: Stabilize and ship. Fix the highest risk issues first, typically CRM sync errors, duplicate management, and broken consent handling. Launch or rebuild at least one priority nurture program on clean segmentation. Establish naming conventions, governance rules, and a change log so every future update stays traceable and safely reversible for your team.
  • Days 61 to 90: Optimize and prove value. Recalibrate lead scoring with sales feedback, launch structured A B tests on subject lines, content, and send times, and stand up funnel and pipeline contribution dashboards. Close the quarter with a leadership readout that ties the work to conversion rates and pipeline outcomes, not activity counts.

Making the Hiring Decision With Confidence

The Interview Signals That Separate Operators From Pretenders

Red flags:

  • Overengineering simple problems. The candidate proposes a sprawling workflow web with dozens of branches for a basic welcome series. Complexity feels impressive in an interview but becomes a maintenance nightmare. Senior operators choose the simplest design that meets the goal and can be explained to anyone on your team.
  • Tool obsession over business outcomes. They talk endlessly about platform features but cannot tell you what a program did for pipeline or conversion. If every answer centers on what the software can do rather than what the business achieved, you are interviewing a user, not an owner.
  • No honest failure stories. Ask about a migration, sync, or deliverability problem that went wrong. Candidates who claim nothing ever broke either lack real ownership or lack candor. Both are dangerous when you hand them the keys to your database and your sender reputation.
  • Ignoring compliance and consent. When asked about Canadian or European contacts, they shrug or defer entirely to legal. Someone who does not understand CASL, GDPR, and CAN SPAM basics will eventually build programs that expose your brand to complaints, blocklisting, and regulatory risk without realizing it.

Green flags:

  • Pragmatic tradeoff analysis. They explain why they chose one scoring approach over another, what it cost, and what they would revisit. They weigh speed against data quality openly. That kind of reasoning shows they will make sound calls when you are not in the room to supervise every decision.
  • Fierce focus on data integrity. They ask about duplicate rates, field governance, and sync direction before discussing campaigns. They know that every downstream report, score, and segment inherits the quality of the underlying data, and they treat the CRM connection with the respect it deserves.
  • Proactive risk identification. Without prompting, they flag deliverability threats, consent gaps, or lifecycle loopholes in your scenario. They propose testing plans and rollback options. This is the instinct that prevents a quiet configuration change from silently breaking attribution across an entire quarter of reporting.
  • Command of edge cases. They know what happens when a contact resubscribes, when a lead converts in the CRM mid nurture, or when two forms update the same field. Fluency with these marketing automation edge cases signals someone who has lived inside production instances, not just demos.

Why Leaders Choose SoftDoes for Marketing Operations Talent

SoftDoes is a North America focused custom software, marketing operations, and data and AI partner serving clients across the US and Canada. We deploy battle tested senior talent with verified marketing automation expertise, every one vetted through campaign builds and real program reviews. You get delivery oversight from experienced marketing operations leads, not unmanaged freelancers. We move fast, scale your team up or down as priorities shift, and back every placement with a zero risk replacement guarantee. When your automation depends on a clean CRM foundation, our Salesforce specialists work alongside your automation experts to keep data, sync, and attribution reliable.

The Bottom Line and Your Next Move

Marketing operations execution is now a direct driver of business performance, and the cost of guessing on this hire compounds every single month. You do not need another lengthy recruiting cycle or a certification holder who has never fixed a broken instance. You need proven operators who deliver measurable pipeline impact quickly. Book a technical discovery session with SoftDoes solution architects, and we will map your bottleneck, define the right profile, and present vetted marketing automation talent ready to start.

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