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Looking to hire a Design Researcher? Our Design Researchers bring senior-level expertise, backed by a U.S. delivery team.
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Discover developers that match your project requirements.No exact match for this specialty yet — here are related experts from our network.
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.
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.
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.
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.
10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.
AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.
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.
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.
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.
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.
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.
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.
What our Design Researchers can build

Which engagement model is right for you?
One engineer, ongoing delivery support, or a complete product team. You set the dial. The firm stands behind every level.

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.
- Senior engineer(s) integrated into your team.
- Fast onboarding into your workflow.
- Flexible monthly engagement.
- Replacement guarantee if needed.
- Direct communication and full transparency.

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).
- SoftDoes delivery oversight.
- Regular technical and delivery check-ins.
- Optional code reviews and QA support.
- Escalation management.
- Replacement support.
- Flexible team scaling.

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.
- Cross-functional collaboration.
- One engagement structure and one point of contact.
- Easy scaling up or down.
- Team continuity throughout the project.

Need the outcome, not the team?
SoftDoes also delivers complete projects end to end.
- End-to-end project ownership.
- Dedicated Project Manager.
- Engineering, QA, Design, and Product expertise.
- Delivery planning and sprint management.
- Quality assurance throughout development.
- Transparent communication and regular progress updates.
- One accountable partner responsible for successful delivery.


Not sure which engagement model fits?
SoftDoes takes full ownership of delivery, combining project management, engineering, design, and QA into one accountable team focused on successful outcomes.
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Engagement Flexibility
Launch with a single senior engineer who can own development from day one. Validate ideas, ship faster, and scale only when your product requires additional capacity.
Expand naturally as new priorities emerge. Bring in frontend, backend, QA, DevOps, or design specialists without disrupting your existing workflow.
Transform individual contributors into a dedicated delivery pod. Combine engineering, QA, design, and product expertise working together toward shared outcomes.
Increase or reduce team size based on roadmap, funding, or workload. Stay lean during quieter periods and scale confidently when demand grows.
How to hire a Design Researcher
Fill out a short form and see who's on the bench. Real profiles, verified histories.
Tell us what you need. We propose two or three candidates from the bench; you interview them directly.
Your engineer starts on your project. Contract, payments, and the guarantee run through us.
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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 take to hire a Design Researcher through SoftDoes?
Traditional enterprise hiring cycles for a senior design researcher often stretch to 8 to 12 weeks from search launch to offer acceptance, and longer for roles requiring deep domain or regulatory expertise. SoftDoes compresses this dramatically by maintaining a pre vetted talent network of senior researchers already evaluated for technical skills, communication skills, and cross functional fit. In most cases, you can be introduced to qualified candidates within days, not months, and have a researcher actively contributing to your project within the first two weeks. This speed does not come at the expense of quality; it comes from eliminating the sourcing, screening, and evaluation bottleneck that slows traditional recruitment.
What does it cost to hire a Design Researcher?
Senior design researchers in the U.S. typically command total compensation averaging around $178,600 per year, with base salary ranges spanning roughly $108K to $175K depending on region, industry, and experience level. Additional compensation in the form of equity, bonuses, and benefits (including vision insurance and other perks) can add substantially at senior levels. Beyond salary, organizations should budget for research tools, participant recruitment, incentives, infrastructure, compliance, and potential travel. SoftDoes engagement models are designed to provide cost transparency and flexibility, so you invest in outcomes rather than carrying the full overhead of a traditional hire during periods when research demand fluctuates.
What engagement models are available (dedicated hire, pod, contract)?
SoftDoes offers three primary engagement models tailored to different business needs. A dedicated hire model places a senior design researcher as a long term extension of your team, ideal for ongoing product development and building a sustained research practice. A pod model deploys a small, integrated research unit (researcher plus supporting roles) for initiatives that require broader coverage across multiple products or squads. A contract model provides focused, time bound research capacity for specific discovery phases, product launches, or validation sprints. Each model offers the flexibility to scale up or down as your project demands shift, without the friction of traditional hiring and termination cycles.
How do you ensure time zone alignment with a Design Researcher?
SoftDoes focuses on North American talent, drawing from the US, Canada, and Latin America. This ensures meaningful overlap with your team's working hours regardless of whether your organization operates on Eastern, Central, Mountain, or Pacific time. For teams with distributed or remote work setups, SoftDoes matches researchers who have proven experience collaborating asynchronously across time zones while maintaining responsiveness during core business hours. Time zone alignment is treated as a core matching criterion, not an afterthought.
How does SoftDoes technically vet a Design Researcher?
Every design researcher in the SoftDoes network undergoes a multi stage technical evaluation that goes far beyond resume review. The process includes a live scenario evaluation where candidates tackle ambiguous, real world product challenges under time constraints. This is followed by an architecture and system design review assessing how candidates would build and scale research operations, data pipelines, and insight repositories. Candidates are then evaluated on communication under pressure, simulating stakeholder pushback on methods, timelines, or budgets. Finally, cross functional fit is assessed through structured interviews involving engineering, product, and design leadership. This pipeline ensures that every researcher deployed has the strategic thinking, technical depth, and collaboration skills required for enterprise environments.
What happens if the Design Researcher isn't the right fit, or I need to scale up or down?
SoftDoes provides a zero risk replacement guarantee. If a deployed design researcher does not meet your performance expectations or is not the right fit for your team's culture and technical environment, SoftDoes replaces them at no additional cost to you. There is no penalty, no drawn out negotiation, and no gap in coverage. Similarly, if your project demands change and you need to scale research capacity up or down, SoftDoes adjusts your engagement model accordingly. This flexibility eliminates the financial and operational risk that makes traditional senior hiring decisions so high stakes, giving you the confidence to invest in research knowing you are protected against mis hires and shifting priorities.
The Executive Guide to Hiring a Design Researcher
A single bad design researcher hire can quietly cost your organization six figures in wasted sprints, failed features, and delayed releases. A great one can compress your product cycle, eliminate rework, and drive measurable revenue gains within the first quarter. This is the field tested playbook for defining, vetting, and onboarding top tier design researcher talent without the executive hiring nightmare.
What Is Actually at Stake When You Hire a Design Researcher
What Separates Senior Design Researcher Talent from Order Takers
Most job descriptions for design researchers read like a shopping list of tools and methodologies. That is exactly why most hires fail. The difference between a highly skilled senior UX researcher and a mid level practitioner who runs usability tests is not about techniques; it is about ownership, strategic thinking, and the ability to solve complex problems under real constraints.
Here is what a true senior design researcher actually does on a daily basis:
- Drives discovery before engineering begins. They define the problem space through generative and evaluative research, user feedback synthesis, ethnography, and quantitative analysis, shaping product strategy before a single line of code is written. Core research methods include both generative and evaluative techniques for effective design research.
- Architects reusable systems of insight. They build research repositories, data pipelines, and frameworks so that actionable insights are not locked in one team's Confluence page but flow across cross functional teams. Design researchers should be able to synthesize data into clear, actionable insights.
- Manages tradeoffs among speed, cost, validity, and compliance. In regulated industries (finance, healthcare, security), this means navigating ethical data handling, participant privacy, and regulatory constraints without grinding the project to a halt. Understanding ethical data handling and participant privacy is crucial for researchers. Ethical judgment is increasingly considered a core competency in research.
- Translates findings into executive level strategy. Strong communication and presentation skills are not optional. Candidates must have strong communication and storytelling skills to make research influence business goals, not just design solutions.
- Operates as a cross functional force multiplier. They collaborate with product managers, developers, legal, compliance, and data science, ensuring research is implemented, not shelved.
- Mentors junior researchers and scales the practice. Senior UX researchers typically have at least five years of experience, often over a decade, and they bring the leadership needed to build a research function, not just fill a seat.
Good researchers can explain the reasoning behind their method choices and recognize limitations. Quality UX researchers excel in both qualitative and quantitative methods, and proficiency in tools like SPSS or R is essential for data analysis. Experience with behavioral analytics tools like Google Analytics is also valuable for connecting user behavior to business outcomes.
The Business Case: Financial and Operational ROI
The financial case for embedding senior design research talent early is not theoretical. Here are the ROI vectors that matter to your P&L:
- Technical and UX debt reduction. Research driven product development identifies pain points and usability failures before they compound into expensive rework cycles. In one enterprise supply chain case, 75% of demo losses were traced to UX failures, not algorithm performance. Investing in user research directly tied to revenue conversion in sales.
- Faster time to market and deployment cycles. A life insurance SaaS platform used discovery research before mapping its feature roadmap and reduced underwriting cycle time from weeks to under one day, securing a Fortune 300 client worth millions annually. Good UX researchers conduct rapid testing and iteration effectively.
- Revenue protection and expansion. A legal tech company built a UX research function that turned design from a cosmetic liability into a renewal and expansion engine. Customers involved in research had significantly higher retention, driving measurable ARR gains.
- Risk mitigation in regulated environments. In finance, healthcare, and e commerce, where compliance failures are existential, a senior user researcher who understands regulatory constraints prevents costly delays and audit failures.
A study of manufacturing firms showed that intensive designer involvement in early stages (market research, concept development) drives product innovativeness and development efficiency, both of which correlate strongly to business performance. Under high market uncertainty, early stage involvement mattered even more for innovation.
Before You Start Searching: Preparing Your Organization
Auditing Your Technical Constraints Before Writing a Single Job Posting
Before you search for applicants, you need to audit three internal dimensions. Skipping this step is the most common reason enterprise design researcher hires fail within the first six months.
Architecture and Debt Audit
What problem must this hire solve first? Identify your existing UX and design debt. Are there legacy platforms, monolithic architectures, or compliance constraints that will define the researcher's first 90 days? If your digital products are built on aging systems with no existing user research infrastructure, your hire needs to be comfortable conducting a full architecture and content audit before they can deliver strategic insights. Define core competencies for design researchers based on needs before writing job descriptions.
Team Dynamics and Autonomy Level
Do you need an embedded specialist inside a single product team, or someone building a centralized research pod that supports multiple squads? This decision affects speed, cost, and the type of candidate you target. An embedded model gives faster cycle times on a single product. A pod model creates leverage across your portfolio but requires more seniority and leadership capability. Experience in cross functional teams is important for design researchers.
Deployment Model Dynamics
Full time in house hires bring continuity but carry the friction of long hiring timelines (often 8 to 12 weeks from search launch to offer acceptance), benefits overhead, and ramp up cost. Remote work models and vetted dedicated talent through partners like SoftDoes can compress deployment timelines dramatically while maintaining alignment and oversight. This is not about choosing between quality and speed; it is about choosing a model that matches your project's urgency and risk tolerance.
Engineering the Ideal Profile, Not a Generic Job Spec
A compelling job description should outline project goals and required skills, but the best profiles go further. Job descriptions should focus on methodology and impact rather than an exhaustive tool list. Four essential components separate a profile that attracts A list talent from one that attracts resume volume:
- Core outcome and mission. Define what specific business problems research will solve. "Reduce feature failure rate by 30%" or "shorten design to engineering handoff from two weeks to three days" are missions. "Conduct user research" is not.
- Technical stack reality. Be honest about the platforms involved, existing design tools and ai tools, data systems, compliance regimes, and AI/ML maturity. Candidates who understand your architecture will self select; those who do not will waste your pipeline.
- Decision making authority. Specify the level of autonomy. Who signs off on research budgets, methods, and designs? What reporting lines exist? How much influence does this role have on product design decisions? Senior candidates will not join organizations where research has no decision rights.
- Growth trajectory and impact path. Where can this role go? Research lead, principal strategist, director of design ops? This matters enormously to the caliber of candidate you attract. A role with no visible growth path will lose top talent to competitors who offer one.

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The Vetting and Onboarding Playbook
A Battle Tested Vetting Framework That Actually Works
Sourcing Reality
Traditional recruiters rarely have the domain knowledge to evaluate a senior design researcher's technical skills or strategic depth. They optimize for resume keywords and availability, not for the ability to contribute meaningfully under real engineering constraints. Demand for UX researchers has tripled since 2013, and one in three UX design job postings is for UX research, meaning the talent market is competitive and noisy. Indeed lists over 1,000 design researcher jobs in New York alone, and LinkedIn features over 1,000 design researcher job postings. The field of UX research shows no signs of losing momentumaa.
Prescreened engineering talent networks, like our talent network, fundamentally change this dynamic. Instead of waiting months and filtering hundreds of applicants, you access professionals already vetted for expertise and communication skills, matched to your technical environment. Hiring should focus on how candidates think rather than the number of techniques they know.
Technical Evaluation Pipeline
Here is the evaluation pipeline that separates signal from noise:
- Live scenario evaluation over trivia. Present an ambiguous product challenge: "You are assigned an enterprise SaaS product with passive user feedback, high regulatory requirements, and three competing stakeholder priorities. Plan your research roadmap." Evaluate problem framing, method choices, tradeoffs, and stakeholder engagement. Use realistic assessments instead of generic tests in the hiring process.
- Architecture and system design review. Ask the candidate how they would build a research platform, data pipelines, and insight repositories across multiple products or teams. Look for knowledge of research ops, data permissions, and centralization versus embedded models.
- Communication under pressure. Simulate stakeholder pushback on cost, timing, or clarity and evaluate how the candidate defends their methods and argues for research value. Evaluate how candidates handle conflicting stakeholder opinions during interviews.
- Cross functional culture fit. Involve cross functional partners in the interview process for better evaluation. History of collaborating with legal, compliance, engineering, and product managers is essential. Conduct structured interviews using mixed methodologies to assess candidates effectively.
Research portfolios should emphasize decision impact over visual polish. Review case studies demonstrating the impact of research on product decisions. Hiring a design researcher requires balancing analytical skills with empathy, and researcher candidates should demonstrate empathy and active listening abilities.
The First 90 Days: A Frictionless Ramp Up Protocol
The hiring process does not end at offer acceptance. Here is the 30/60/90 day milestone roadmap that ensures immediate ROI and ownership:
- Days 1 through 30: Discovery and alignment. Meet product, engineering, and legal stakeholders. Audit current UX and research maturity. Define two to three short research bets to deliver early insight. Identify quick wins that build credibility and stakeholder trust.
- Days 31 through 60: Foundation building. Execute foundational research: user interviews, heuristic evaluations, content and system audits. Build an early research roadmap tied to business goals. Define metrics and KPIs. Establish infrastructure including participant pools, repositories, and training for adjacent teams.
- Days 61 through 90: Strategic delivery. Deliver the first strategic insights that influence the product roadmap. Ensure implementation of findings across development teams. Establish visibility with executive stakeholders. Set up processes for continuous user feedback loops. Plan extension or scaling of the research practice.
This protocol is designed so that by day 90, your design researcher has delivered measurable value, not just "completed onboarding."
Making the Decision: Signals, Advantage, and Next Steps
Interview Signals That Predict Success or Failure
Red flags that predict a costly mis hire:
- Tool obsession over problem solving. "I only use UserZoom" or an inability to discuss tradeoffs between methods signals rigidity. Mid level researchers are familiar with tools like UserZoom and Hotjar, but seniority demands flexibility and judgment.
- Inability to discuss past failures. Every experienced researcher has had a study fail or a recommendation ignored. Candidates who cannot discuss what went wrong and what they learned are a risk.
- Overemphasis on qualitative only. UX researchers should be proficient in both qualitative and quantitative methods. A candidate who cannot discuss quantitative validation is missing half the picture.
- Weak connection to business metrics. If a candidate cannot articulate how their research influenced customer satisfaction, retention, revenue, or time to market, their prior experience likely had limited strategic impact. Business acumen is important for balancing user needs with product goals.
Green flags that predict a significant impact hire:
- Pragmatic tradeoff analysis. The candidate proactively discusses speed versus validity, cost versus fidelity, and compliance versus agility, showing they understand the real constraints of enterprise product design.
- Focus on data integrity and system thinking. They talk about building reusable research infrastructure, not just running one off studies. They think about how insights flow across teams and create user centered design at scale.
- Proactive risk identification. They ask about compliance, data privacy, legacy architecture, and stakeholder alignment before you bring it up. Design researchers should clarify whether foundational or evaluative research is needed for the specific context.
- Evidence of shaping product strategy. They can point to specific instances where their research changed a roadmap, killed a feature, or opened a new market segment. UX researchers help shape design processes across various industries. UX research is critical for user centered design in tech sectors.
Why SoftDoes Is the Strategic Advantage for Design Researcher Hiring
SoftDoes is a North America focused custom software engineering, data, and AI partner serving clients across the US and Canada. When it comes to placing design researchers, the difference is structural:
- Battle tested senior talent, not unmanaged freelancers. Every researcher deployed through SoftDoes has domain expertise and technical oversight. They integrate with your engineering and product teams as a true extension, not a contractor waiting for direction. Through our product design services, we ensure researchers understand the full product development lifecycle.
- Engineering led delivery oversight. Research quality is monitored and managed. You get executive level reporting, not silence between invoices.
- Rapid deployment capability. Access pre vetted, senior design researchers ready to start within days, not the 8 to 12 week cycle of traditional recruitment. Browse our available designers and researchers to see the caliber of talent ready for deployment.
- Flexible scaling. Dedicated hire, pod, or contract. Scale up when a product launch demands it, scale down when discovery wraps. No long term commitments that create overhead.
- Zero risk replacement guarantee. If the researcher is not the right fit, SoftDoes replaces them at no additional cost. This eliminates the single biggest financial risk in senior hiring.
- Cross domain expertise. Finance, healthcare, e commerce, and other regulated industries. Your researcher arrives with prior experience navigating compliance, data complexity, and the user experiences unique to your sector.
The Bottom Line: Your Next Move
Every week without embedded design research is a week your product team ships features based on assumptions instead of evidence. The cost of a bad hire or a slow hiring process is measured in failed releases, lost deals, and compounding UX debt.
If you are ready to stop treating research as an afterthought and start deploying it as a competitive weapon, the next step is simple: book a technical discovery session with SoftDoes architects. We will audit your current needs, define the perfect match for your team, and deploy senior research talent that delivers from day one.










































