💻 Full-Stack Software Engineer at ScienceSoft USA Corporation – AI, Cloud and Distributed Systems Role
💻 Full-Stack Software Engineer at ScienceSoft USA Corporation – AI, Cloud and Distributed Systems Role. ScienceSoft USA Corporation is hiring a Full-Stack Software Engineer for a senior, high-ownership engineering opportunity focused on artificial intelligence, cloud platforms, distributed systems and modern full-stack application development.
The position is particularly notable because ScienceSoft is not looking for a conventional developer who simply completes assigned coding tasks. The company describes its ideal candidate as an “AI native builder” who incorporates modern AI tools into everyday software engineering to accelerate coding, testing, debugging, prototyping and documentation.
The successful candidate will operate at Staff Software Engineer level, working across backend services, frontend applications, APIs, integrations, workflow orchestration and broader platform architecture.
📌 Opportunity Overview
| Detail | Information |
|---|---|
| Company | ScienceSoft USA Corporation |
| Position | Full-Stack Software Engineer |
| Level | Staff / Senior-level engineering |
| Career Area | Software Development |
| Experience | 8+ years |
| Backend | Python |
| Frontend | React, Next.js or similar |
| Cloud | AWS, Azure or GCP |
| Architecture | Microservices, distributed & event-driven systems |
| AI | AI-assisted development and AI-enabled products |
| Preferred Industry | Fintech / regulated environments |
| Employment focus | Platform development, architecture & integrations |
| Application | Through ScienceSoft Careers |
ScienceSoft’s careers portal currently lists Full-Stack Software Engineer among its open Development vacancies.
About ScienceSoft USA Corporation
ScienceSoft USA Corporation, doing business as ScienceSoft, is an AI transformation and software development company founded in 1989.
The company reports 37 years in IT, approximately 750 IT professionals and more than 4,300 completed projects/success stories. It provides software engineering and technology services across more than 30 industries.
Its engineering expertise includes:
Software Engineering | Artificial Intelligence | Data Science | Cloud | DevOps | Cybersecurity | QA | Data Analytics | Enterprise Applications
ScienceSoft says its software engineering team includes more than 500 developers, with over half at senior or lead level and experienced in technologies ranging from Python, Java and .NET to JavaScript, React and cloud-native architectures.
🚀 What Is the Full-Stack Software Engineer Role?
💻 Full-Stack Software Engineer at ScienceSoft USA Corporation – AI, Cloud and Distributed Systems Role
This is a senior engineering position with significant responsibility for the design and development of ScienceSoft’s platform.
The engineer will work across:
Backend systems
Frontend applications
APIs
Workflows
Integrations
Platform foundations
Rather than concentrating exclusively on either frontend or backend development, the engineer is expected to understand the entire product and technical environment.
That means thinking beyond individual tickets or isolated pieces of code.
ScienceSoft specifically wants someone capable of turning complicated business and technical requirements into reliable product outcomes.
🤖 AI-Native Software Engineering
One of the most interesting aspects of the vacancy is its emphasis on AI.
ScienceSoft explicitly states:
“We are not looking for a traditional software engineer only.”
Instead, the company wants an engineer who uses modern AI tools as part of the daily development workflow.
AI can be used to accelerate:
- Software design
- Coding
- Testing
- Debugging
- Documentation
- Prototyping
- Development and delivery
The engineer will also help improve the team’s broader AI-native engineering practices.
This reflects an important change occurring across software engineering in 2026: developers are increasingly expected not merely to understand AI but to know how to use it productively during software development.
🧠 Which AI Tools Are Relevant?
ScienceSoft specifically identifies experience with AI development tools such as:
Cursor | GitHub Copilot | Claude | Lovable | Replit
or similar platforms as a preferred qualification.
However, simply having used an AI coding assistant is unlikely to be sufficient for a staff-level position.
Candidates should ideally demonstrate how they have used AI to improve real engineering outcomes—for example:
Accelerating prototypes
Generating and improving tests
Exploring architecture
Supporting debugging
Improving documentation
Automating development workflows
ScienceSoft also prefers candidates who have experience building AI-assisted or AI-enabled products, developer tools, internal platforms, agentic workflows or automation systems.
🐍 Strong Python Experience Required
💻 Full-Stack Software Engineer at ScienceSoft USA Corporation – AI, Cloud and Distributed Systems Role
Python is one of the most important technical requirements.
ScienceSoft specifically requires:
Strong backend development experience in Python.
Candidates should therefore be comfortable building and operating production backend systems rather than merely using Python for scripts or basic data analysis.
Strong candidates may have experience involving:
Backend APIs | Distributed services | Databases | Authentication | Integrations | Event processing | Cloud applications
Because this is a staff-level position, architectural understanding is likely to matter just as much as programming ability.
⚛️ Frontend Development
Candidates also need strong frontend engineering capabilities.
ScienceSoft identifies experience with modern frameworks such as:
React
and
Next.js
or comparable technologies.
The engineer will help develop frontend applications, dashboards and internal tools while ensuring they work effectively with backend services and APIs.
This is what makes the position genuinely full-stack.
The successful engineer needs to understand the journey from:
User interface → API → Business logic → Services → Data → External integrations
rather than specializing exclusively in one layer.
☁️ Cloud Engineering Experience
Cloud expertise is another major requirement.
ScienceSoft expects hands-on experience with platforms such as:
Amazon Web Services – AWS
Microsoft Azure
Google Cloud Platform – GCP
The engineer should also understand containerized deployment patterns.
This means candidates should be comfortable thinking beyond application development to questions involving deployment, scaling, monitoring, resilience and production operations.
ScienceSoft’s broader engineering workforce builds cloud-native applications using microservices, serverless and event-driven architectures across AWS, Azure and GCP.
🏗️ Distributed Systems and Microservices
💻 Full-Stack Software Engineer at ScienceSoft USA Corporation – AI, Cloud and Distributed Systems Role
This is not a basic web-development position.
ScienceSoft requires deep experience with:
Service-oriented or microservices architectures
along with strong knowledge of:
API design | Event-driven systems | Workflow orchestration | Distributed-system patterns.
Distributed systems introduce engineering challenges that do not necessarily exist in smaller standalone applications.
Engineers need to consider issues such as:
Service failures
Network reliability
Data consistency
Retries
Observability
Performance
Security
Scalability
The successful candidate is therefore expected to understand how complex production platforms behave as complete systems.
🔗 API and Third-Party Integrations
Another major responsibility involves integrations.
The engineer will help design integrations between ScienceSoft’s platform and:
- Third-party platforms
- Enterprise systems
- Identity providers
- Financial systems
- External services.
This requires more than knowing how to send an API request.
Enterprise integrations must operate reliably, securely and at scale.
Candidates with previous experience integrating payment systems, identity providers, financial platforms, SaaS applications or enterprise systems may therefore have a significant advantage.
🔄 Workflow Orchestration
ScienceSoft places unusual emphasis on workflow orchestration.
Preferred experience includes platforms such as:
Temporal | Zeebe | Camunda
or similar workflow engines.
The company specifically identifies a background in fintech and Temporal orchestration among its preferred qualifications.
Workflow orchestration is particularly useful when business processes require multiple systems and services to coordinate reliably.
This could involve processes such as:
User onboarding → Identity verification → Compliance checks → Account creation → Notifications
Each step may involve a separate service or provider.
The engineer needs to design systems capable of coordinating those processes reliably.
💳 Fintech Experience Is Preferred
💻 Full-Stack Software Engineer at ScienceSoft USA Corporation – AI, Cloud and Distributed Systems Role
Candidates with a fintech background may be especially competitive.
ScienceSoft lists experience in regulated environments such as:
Fintech | Enterprise software | Digital platforms | Other compliance-sensitive industries
as preferred.
This connects directly with other preferred capabilities involving:
- Identity
- Access management
- Auditability
- Policy-driven systems
Regulated industries require engineers to think beyond functionality.
Systems must also satisfy requirements around security, privacy, traceability and compliance.
🔐 Security and Reliability
ScienceSoft requires a strong understanding of:
Security
Reliability
Resilience
Observability
Performance at scale.
These skills are especially important for staff-level engineers.
Building software that works during development is relatively easy compared with building software that remains dependable under real production workloads.
Engineers need to understand how systems behave when:
Traffic increases
Services fail
External APIs become unavailable
Networks become unreliable
Security threats emerge
Databases experience problems
This position therefore requires significant production-engineering experience.
🎯 Key Responsibilities
The successful engineer will help lead development of core platform services, APIs, frontend applications, dashboards and internal tools.
Other major responsibilities include:
- Designing full-stack solutions
- Developing workflow logic
- Building external integrations
- Using AI throughout the development lifecycle
- Working with product and design teams
- Collaborating with security and business teams
- Improving architecture standards
- Improving testing and code quality
- Strengthening observability
- Improving operational excellence
- Mentoring other engineers
- Contributing to long-term platform strategy.
The engineer will also contribute to build-versus-buy decisions, extensibility and long-term maintainability.
🎓 Experience Requirements
This is clearly an experienced-hire opportunity.
Candidates need:
8+ years of software engineering experience
with strong experience building and operating production systems.
ScienceSoft also expects candidates to have worked at:
Senior or Staff level
on complex distributed platforms.
Applicants should therefore have significant professional engineering experience and evidence that they have taken ownership of substantial technical systems.
💼 Minimum Qualifications
ScienceSoft’s key requirements include:
8+ years of software engineering experience
Senior/staff-level distributed-platform experience
Strong full-stack engineering
Strong Python backend development
React, Next.js or comparable frontend expertise
Microservices/service-oriented architecture
API design
Event-driven systems
Workflow orchestration
Distributed systems
Third-party integrations
AWS, Azure or GCP
Containerized deployment
Security and reliability
Observability and performance
Effective use of AI development tools
Strong product thinking.
This is therefore a technically demanding opportunity.
⭐ Preferred Qualifications
Candidates can strengthen their profiles with experience involving:
Fintech
Temporal orchestration
AI-enabled products
AI agents
Developer tools
Automation systems
Cursor
GitHub Copilot
Claude
Lovable
Replit
Regulated industries
Identity and access management
Auditability
Zeebe
Camunda
Platform engineering
Internal developer platforms.
Leadership and mentorship experience are also highly valued.
👩💻 This Is More Than a Coding Job
One phrase in ScienceSoft’s requirements is particularly revealing.
Candidates should be able to think beyond assigned tickets toward:
Customer outcomes, platform value and business impact.
That is a key difference between mid-level and staff-level software engineering.
The company is not simply looking for someone who receives a specification and writes code.
The engineer needs to understand:
Why is this being built?
Is this architecture appropriate?
Should we build or buy?
How will it scale?
What are the security implications?
How will engineers maintain it three years from now?
That broader technical judgment is central to the opportunity.
🤝 Engineering Leadership and Mentorship
💻 Full-Stack Software Engineer at ScienceSoft USA Corporation – AI, Cloud and Distributed Systems Role
The engineer will also mentor colleagues and help raise technical standards across the team.
ScienceSoft’s wider hiring philosophy emphasizes engineers who demonstrate ownership, problem-solving ability, clear communication and the ability to deliver in demanding environments. The company says its hiring process is highly selective.
Candidates should therefore be prepared to demonstrate both technical depth and leadership capability during recruitment.
💰 What Is the Salary?
The official Full-Stack Software Engineer vacancy reviewed for this article does not publish a specific salary range.
Candidates should therefore avoid treating figures from third-party salary websites as guaranteed compensation for this particular position.
The authoritative salary, employment conditions and benefits should come directly from ScienceSoft during the recruitment process.
📝 How to Strengthen Your Application
Because ScienceSoft wants an experienced staff-level engineer, a CV should demonstrate engineering impact, not simply list technologies.
Instead of:
“Worked with Python, React and AWS.”
A stronger achievement would explain the system you built and its scale.
For example:
“Designed a Python microservices platform deployed on AWS supporting high-volume transactions and integrated with five external enterprise APIs.”
Where possible, quantify:
Users | Transactions | Services | Team size | Availability | Performance improvements | Cost reductions
Candidates should also show examples of architectural ownership.
🤖 Demonstrate Real AI Engineering Experience
Don’t simply add:
“Experienced with GitHub Copilot.”
Explain how AI improved your engineering workflow.
Examples might include using AI for:
Automated test generation
Prototype development
Code review assistance
Documentation
Debugging
Architecture exploration
Agentic workflows
Developer productivity
ScienceSoft specifically wants engineers who can use AI to deliver better software outcomes—not candidates who simply know the names of popular AI tools.
Python + Full Stack + Distributed Systems + Cloud + AI + Architecture
If you have fintech, Temporal, AI-agent or regulated-industry experience, make those capabilities particularly visible.
Final Thoughts
💻 Full-Stack Software Engineer at ScienceSoft USA Corporation – AI, Cloud and Distributed Systems Role
The Full-Stack Software Engineer opportunity at ScienceSoft USA Corporation is a strong example of how senior software engineering roles are evolving in 2026.
The company is looking beyond conventional full-stack development.
It wants an experienced engineer capable of combining:
Python + React + Cloud + Distributed Systems + AI + Engineering Leadership
The requirement for 8+ years of software engineering experience makes this a senior opportunity rather than an entry-level position. Candidates should have experience operating production systems and working at senior or staff level on complex distributed platforms.
The AI component is particularly important. ScienceSoft expects the engineer to incorporate modern AI tools into coding, testing, debugging, documentation, prototyping and delivery while also helping the wider engineering team improve its AI-native development practices.
🚨 Key Details
🏢 Company: ScienceSoft USA Corporation
💻 Position: Full-Stack Software Engineer
📊 Level: Staff / Senior
💼 Experience: 8+ years
🐍 Backend: Python
⚛️ Frontend: React, Next.js or similar
☁️ Cloud: AWS, Azure or GCP
🏗️ Architecture: Microservices & distributed systems
🔄 Orchestration: Temporal, Zeebe, Camunda or similar preferred
🤖 AI: AI-assisted engineering, agentic workflows & automation
💳 Fintech: Preferred
🔐 Security: Strong security, reliability and observability knowledge required
💰 Salary: Not publicly specified in the official posting
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