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Hire remote Mach Ii Developer

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

Aditya P.
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Aditya P.Verified in SoftDoes
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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.
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Andrea M.Verified in SoftDoes
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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.
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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.
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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.
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10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

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

Mario J.
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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.
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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.
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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.
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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.
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Tzechung K.
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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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Which Engagement Model Is Right For You?

Whether you need one engineer, ongoing delivery support, or a complete product team, we have an engagement model that fits.

Dedicated Talent

Strengthen your existing engineering team with senior specialists who integrate seamlessly into your workflows while you retain full ownership of priorities, roadmap, and day-to-day management.

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Managed Talent

Ideal for teams that need experienced engineers backed by technical leadership, ensuring faster onboarding, predictable execution, and consistent delivery without adding management overhead.

  • Dedicated senior engineer(s).
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Launch products faster with a ready-to-work cross-functional team that brings together the right expertise from day one, helping you scale without the complexity of hiring each role individually.

  • Engineers, QA, Designers, PMs, Tech Leads - assembled to fit your project.
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  • One engagement structure and one point of contact.
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Eugene M.DevOps EngineerAWS / GCP / Terraform / Gitlab
AWS / GCP / Terraform / Gitlab
Rate$53 / hour
LanguagesEnglish
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Frequently Asked Questions

Everything you need to know about working with SoftDoes. Can’t find an answer?

How long does it typically take to hire developers with proven Mach II expertise?

Through traditional recruiting, finding a qualified Mach II engineer can take several months, because the talent pool is small, senior, and mostly employed already. Many searches end with compromise hires who know CFML but have never worked inside an event driven Mach II configuration. Working with a pre vetted network shortens the timeline considerably. SoftDoes typically presents a short list of matched senior engineers within days, and once you approve a candidate, onboarding can begin almost immediately. The biggest variable on your side is how quickly you can provide repository and server access, schedule interviews, and confirm the scope of the work.

What does it cost to hire a developer or team with deep Mach II expertise?

Cost depends on seniority, engagement length, team size, and the complexity of the work. Routine maintenance on a stable application costs less than security remediation or a phased migration that needs several engineers working in parallel. Because real Mach II experience is scarce, specialists usually command senior rates, but they also resolve problems far faster than generalists who must learn the framework on your budget. SoftDoes provides transparent pricing after a short discovery conversation, so you see a clear estimate tied to your actual scope rather than a generic rate card. Flexible models let you match spending to the outcomes you need.

What engagement models are available for Mach II projects, such as a dedicated hire, a pod, or a contract?

SoftDoes offers several options so you can match the engagement to your situation. A dedicated specialist works as an extension of your team, ideal for ongoing maintenance and gradual improvements on a stable application. A pod combines a lead engineer, supporting developers, and QA, which suits larger codebases, security remediation projects, or migrations running alongside daily support. A fixed scope contract works well for clearly defined work, such as an architecture audit or a single module migration. You can start small and change models as your needs evolve, and our scaling guarantees keep transitions smooth without restarting the hiring process from scratch.

How do you ensure time zone alignment with a team skilled in Mach II?

SoftDoes focuses on clients across the US and Canada, so we build teams with working hours that overlap meaningfully with yours. Before an engagement starts, we agree on core collaboration hours, meeting rhythms, and response expectations, and we match engineers whose schedules support those commitments. That overlap matters for legacy work in particular, because questions about undocumented behavior in a Mach II application often need quick answers from your internal experts. We also set up shared communication channels, clear ticketing workflows, and written handoff notes, so progress continues smoothly and nobody waits a full day for a simple clarification.

How does SoftDoes technically vet developers for Mach II expertise?

Our vetting goes well beyond resume screening. Candidates walk through a real XML configuration and explain how requests move through events, filters, listeners, and views, then describe where they would place new logic and why. They complete practical tasks such as refactoring an unsafe query with cfqueryparam, adding TestBox coverage to a listener, or outlining a strangler migration plan toward ColdBox or another stack. We assess how they reason under constraints like zero downtime, and we evaluate communication, documentation habits, and patience with legacy code. Only engineers who pass every stage join our network and become available to clients.

What support is available for scaling the team after launch as our Mach II needs grow?

Needs change once the first improvements land. You might move from stabilization into a full migration, or a security audit might reveal more work than expected. SoftDoes lets you add engineers, QA, or a technical lead without starting a new recruiting cycle, drawing on the same pre vetted network that supplied your original team. Because we work as a team model, new members onboard faster using the documentation and context the existing engineers already built. You can also scale down when the workload eases, and our replacement guarantee means any engineer who is not the right fit is swapped quickly.

How to Hire Developers Skilled in Mach II

Most companies running a Mach II application learn the hard way what an underqualified hire costs. A generalist opens the XML configuration, guesses at the event flow, patches a listener, and quietly breaks three views nobody tested. The release slips, a security finding stays open, and the legacy system becomes even harder to touch. The right Mach II ColdFusion developer does the opposite: stabilizes the platform, closes risks, and plans a calm path forward. This guide shows you how to define the role, source and vet real Mach II specialists, onboard them quickly, and spot the signals that separate experts from pretenders.

What Mach II Really Does Inside Your Business

The Daily Engineering Work Behind a Healthy Mach II Application

Mach II is an open source, object oriented MVC framework for ColdFusion (CFML). An XML configuration file maps every event to listeners, filters, and views, so the framework decides how each request moves through your application. The project is no longer actively developed, which means production work today centers on maintaining, stabilizing, and migrating existing systems rather than starting new ones. Typical tasks include:

  • Tracing and documenting the event flow. Reading the XML configuration to map each event handler, listener call, filter, and view, then turning that map into documentation your wider team can use when planning changes, estimating effort, or debugging production incidents under pressure.
  • Untangling business logic. Moving rules that leaked into views back into listener CFCs or a proper service layer, so logic lives in one predictable place, can be tested in isolation, and no longer breaks every time someone edits a template or changes page layout.
  • Closing security gaps. Finding raw SQL built from request variables and rewriting those queries with cfqueryparam, removing deprecated CFML tags, and hardening plugins and filters that run on every request, which together shrink the attack surface of an application that may have gone years without review.
  • Managing modules, subroutines, and caching. Working with the features later Mach II versions added, including modules, subroutines, caching, and logging packages, plus ColdSpring dependency injection wiring, so performance stays predictable and new developers can follow how objects are created and shared across requests.
  • Adding automated test coverage. Introducing TestBox around listeners and service components before any refactor begins, building a safety net that catches regressions early and lets the team change old code with confidence instead of relying on slow manual clicking through every critical screen and workflow.
  • Planning and executing migration. Moving functionality gradually to ColdBox or to a stack such as Java, .NET, Node, or Python using a strangler approach, routing one feature at a time to the new system while the existing Mach II application keeps serving customers without a risky big bang cutover.

Why Real Mach II Expertise Protects Revenue and Roadmaps

  • System stability. An engineer who understands the event lifecycle can diagnose failures in plugins, filters, and listeners quickly instead of guessing. That shortens outages, reduces repeat incidents, and keeps the customer facing workflows that depend on this application running reliably while the rest of your roadmap moves forward.
  • Faster, safer delivery. When someone can read the XML configuration and predict exactly what a change will touch, small fixes stop turning into week long investigations. Releases become routine again, your product team can commit to dates, and the legacy platform stops blocking work elsewhere in the business.
  • Lower technical debt and security risk. Experienced specialists replace deprecated tags, parameterize queries, and move the app off unsupported ColdFusion versions onto supported Adobe ColdFusion or Lucee. Each step removes a patching or hosting liability that would otherwise grow quietly until an audit or incident forces an expensive emergency response.
  • A realistic path to modern architecture. Deep knowledge of how the current system behaves is the foundation of any credible migration plan. An expert can sequence the move to ColdBox or another stack feature by feature, protecting data integrity and keeping the business running while the old framework is retired.

Getting Your House in Order Before You Hire

Clarify What Your Mach II System Actually Needs

Before you open a requisition, decide what success looks like for this application over the next stage of its life. Are you keeping it alive for years, stabilizing it before a sale or audit, or preparing a full migration? Each goal calls for a different profile. If you already know the long term plan includes rebuilding core functionality, align the hire with your broader custom software development strategy so maintenance work and new build work point in the same direction instead of competing for budget.

Map the Scope, Risks, and Target Architecture

Start with a short internal audit. List the Mach II version you run, the ColdFusion or Lucee engine underneath it, the number of events and listeners in the XML configuration, and any modules or ColdSpring wiring involved. Note known pain points: slow pages, recurring errors, unpatched servers, or business rules hidden in views. Then state the target architecture plainly. Staying on Mach II with better tests is one scope; moving gradually to ColdBox is another; a strangler rewrite to Java, .NET, Node, or Python is a third. Candidates and partners can only estimate accurately when this picture is written down.

Choose the Right Seniority and Supporting Skills

Mach II work is rarely suitable for junior engineers. The code is often old, lightly documented, and full of decisions nobody remembers making, so you need someone senior enough to work independently and make careful judgment calls. Beyond CFML and Mach II itself, look for strong SQL skills, familiarity with ColdSpring, TestBox experience, and comfort with server administration on Adobe ColdFusion or Lucee. If migration is on the roadmap, add knowledge of ColdBox or your chosen target stack. Because true Mach II specialists are scarce, a strong CFML engineer who reads XML event flow quickly can be a smart alternative.

Decide Between an In House Hire and a Dedicated Remote Pod

A single in house hire works when the application is small, stable, and only needs steady maintenance. The risk is concentration: one person holds all the knowledge, and if they leave, you start again. A dedicated remote pod spreads that knowledge across a lead engineer, supporting developers, and QA, which suits larger codebases, security remediation projects, or migrations running in parallel with daily support. Pods also scale up or down without new recruiting cycles. Weigh the size of your backlog, how fast you need results, and how much management time your internal leaders can realistically give.

Writing a Role Profile That Attracts Genuine Mach II Experts

  • The technical mission. State exactly what the engineer will accomplish: stabilize a revenue critical Mach II application, remediate security findings, add test coverage, or lead a phased migration. A clear mission filters out generalists and tells experienced Mach II ColdFusion developer candidates that you understand the real work involved.
  • The ecosystem and tooling. Name the Mach II version, the ColdFusion or Lucee engine and version, the database, source control, deployment process, and whether ColdSpring or TestBox is already in place. Specific detail signals a serious opportunity and helps candidates judge honestly whether their experience genuinely matches your environment.
  • Team dynamics. Explain who the engineer reports to, which developers and product owners they will work with, how decisions are made, and how much autonomy they will have. Legacy work needs someone comfortable asking hard questions, so describe how open your team is to challenge and documentation improvements.
  • System impact. Describe what the application does for the business, how many users rely on it, and what happens when it fails. Engineers who understand the stakes make better tradeoffs, and candidates motivated by meaningful outcomes are more likely to stay through the difficult parts of a legacy engagement.
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Sourcing, Vetting, and Ramping Up Your Mach II Team

A Hiring Process Built for a Small, Senior Talent Pool

Where to Find Engineers Who Have Shipped Mach II Code

Standard outbound recruiting struggles here. Job boards rarely surface Mach II experience, keyword searches return outdated profiles, and the few qualified engineers are usually already employed. Expect long cycles and many screening calls that go nowhere. A pre vetted network with a proven CFML and Mach II track record removes most of that friction, because candidates have already been tested on real legacy work. Working through an established talent network lets you review a short list of senior engineers in days rather than months, and focus your energy on fit instead of filtering hundreds of unqualified applications.

How to Test Mach II Skill Beyond the Resume

Resumes say little about how someone handles a tangled legacy codebase. Ask candidates to walk through a sample XML configuration and explain how a request moves through events, filters, listeners, and views, and where they would place new logic. Give a practical task, such as refactoring a listener with an unsafe query into a parameterized, tested component, or sketching a strangler migration plan for one module. Add a constraint, like no downtime allowed, and watch how they reason. Finally, assess culture fit: patience with old code, clear written communication, and willingness to document what they discover.

A 30/60/90 Day Plan to Get Productive Fast

  • Days 1 to 30: access and discovery. Grant repository, server, database, and ticketing access on day one. The engineer maps the XML event flow, documents listeners and plugins, sets up a local Lucee or ColdFusion environment, and ships a small low risk fix to prove the deployment pipeline works end to end without surprises.
  • Days 31 to 60: stabilization. The engineer adds TestBox coverage around the most critical listeners, parameterizes risky queries, and resolves the top recurring errors. Weekly check ins with your technical lead keep priorities aligned, and every change is documented so knowledge stops living in one person's head and spreads across the team.
  • Days 61 to 90: ownership and roadmap. The engineer or pod now owns releases for the Mach II application and presents a written plan covering remaining debt, engine upgrades, and migration options. You should see predictable delivery, fewer incidents, and a clear, costed recommendation for the next stage of the system.

Choosing With Confidence

Warning Signs and Strong Signals in Mach II Interviews

Red flags:

  • The candidate cannot explain how events, listeners, filters, and views connect in the XML configuration, or treats Mach II like a generic CFML app. Without that mental model, every change becomes guesswork and regressions multiply quickly in production.
  • They suggest rewriting everything immediately without assessing risk, data, or business continuity. Big bang rewrites of legacy systems often stall, and a candidate who skips incremental options has likely not lived through one.
  • They show no concern about raw SQL, unsupported ColdFusion versions, or missing patches. Ignoring security basics in an older application signals inexperience with the real liabilities that legacy CFML systems carry.
  • They have never written automated tests for CFML code and dismiss TestBox as unnecessary. Refactoring old Mach II code without a safety net is how small fixes become outages.

Green flags:

  • They ask which Mach II version, engine, and ColdSpring setup you run before proposing anything. Good questions early show they know these details change the approach and the effort required.
  • They can describe moving logic out of views into listeners or services and explain why it matters for testing and maintenance, using concrete examples from past legacy work.
  • They propose a strangler migration toward ColdBox or another stack, with clear steps, rollback points, and a plan for keeping the current system serving users throughout the transition.
  • They write clearly, document as they go, and talk about leaving the codebase easier for the next engineer. That habit is the strongest predictor of lasting value on legacy platforms.

What SoftDoes Brings to Your Mach II Project

SoftDoes is a North America focused software engineering and talent delivery partner serving clients across the US and Canada. We give you immediate access to pre vetted senior engineers who have maintained and migrated real CFML systems, including Mach II applications. Instead of placing isolated freelancers, we deliver through a team model, so knowledge is shared and your project never depends on one person. Every engagement includes replacement and scaling guarantees, and you can start with one specialist or a full pod. If your needs extend across the wider CFML ecosystem, you can also hire ColdFusion developers through the same vetted process.

Let's Talk About Your Mach II Application

Your Mach II system does not have to be a source of risk and delay. Whether you need to stabilize it, secure it, or plan a careful migration, the right engineers make the difference between constant firefighting and steady progress. Schedule a discovery call with SoftDoes today. We will review your application, discuss your goals, and recommend the team setup that fits your timeline and budget, so you can move forward with confidence.

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