Senior Software Engineer - Remote Latam

Location: Remote | LATAM

Employment Type: Full-Time

Overview

We are seeking aSoftware Engineer IV with 10+ years of professional software development experience to design and build high-impact tools that improve how our SaaS platform is configured, implemented, validated, and delivered to customers.

This is a highly technical, hands-on role focused on solving complex engineering problems and creating scalable tools for both internal implementation teams and customers. The engineer will work on tools that help implementation teams configure and manage the product, as well as client-facing capabilities that enable customers to validate and prepare their data before it is handed over for implementation.

A key focus of the role will be performance at scale, including designing and optimizing applications that work with very large datasets-potentially 100+ million records. The successful candidate must be comfortable reasoning about database performance, application architecture, data processing, scalability, and system efficiency at this level. AI-assisted development is an important part of how we work. Claude is our approved internal AI coding tool, and this role will use AI to accelerate implementation, testing, refactoring, debugging, and documentation. However, AI is a development accelerator-not a substitute for engineering judgment. You will be responsible for defining the problem, creating clear specifications, validating AI-generated output, and owning the quality of the final solution.

This role is ideal for an engineer who combines deep technical expertise, architectural thinking, strong hands-on development skills, and a genuine passion for software engineering.

What You’ll Build

You will design and develop tools that directly improve the efficiency, quality, and scalability of our SaaS implementation process.

Examples include:

• Internal implementation tools that help teams configure, manage, and deploy the product more efficiently.

• Client-facing data validation tools that allow customers to identify and resolve data issues before submitting data for implementation.

• Tools and services that reduce manual implementation effort and improve operational efficiency.

• Scalable applications and services capable of processing and working with very large datasets.

• Technical capabilities that support a high volume of customer implementations and go-live activities.

• Engineering solutions that can be adopted broadly across internal teams and customers.

Key Responsibilities

Architecture & Software Engineering

• Lead the design and implementation of complex tools, features, services, and technical initiatives across the SaaS platform.

• Design scalable, reliable, and maintainable applications using C#, .NET,ASP.NETMVC, and Blazor.

• Make architectural and technical decisions that support long-term scalability, performance, maintainability, and reliability.

• Design and develop APIs, services, integrations, and distributed application components.

• Apply sound software engineering principles, including SOLID principles, design patterns, separation of concerns, and maintainable architecture.

• Evaluate technical approaches and select solutions based on business requirements, system constraints, performance, and long-term maintainability.

• Translate clearly defined product and business requirements into robust technical designs and implementations.

• Partner with Product and implementation stakeholders to clarify requirements and identify the best technical approach without taking ownership of product management responsibilities.

Large-Scale Data & Performance

• Design and optimize applications that operate against very large datasets, including datasets exceeding 100 million records.

• Identify and resolve database, application, API, and architectural performance bottlenecks.

• Design efficient data access, processing, querying, and transformation strategies.

• Analyze system behavior under high data volumes and identify opportunities for significant performance improvements.

• Develop solutions that remain responsive, reliable, and scalable as data volumes and customer usage increase.

• Use profiling, monitoring, benchmarking, and other engineering techniques to validate performance improvements.

• Balance performance optimization with maintainability, reliability, and development velocity.

AI-Assisted Development

• Use Claude, the organization’s approved AI coding assistant, to accelerate development and engineering workflows.

• Apply AI to appropriate development activities, including coding, refactoring, debugging, test generation, documentation, and technical exploration.

• Create clear technical specifications, acceptance criteria, and implementation requirements that provide AI coding tools with sufficient context.

• Review and validate AI-generated code for correctness, security, performance, maintainability, and architectural fit.

• Use independent engineering judgment to determine when AI-generated solutions require modification, rejection, or deeper technical investigation.

• Help establish effective team practices for AI-assisted development while maintaining appropriate human review and accountability.

• Continuously evaluate how AI can improve engineering efficiency without compromising software quality.

Technical Leadership Mindset

• Act as a senior technical authority for complex engineering and architectural challenges.

• Provide technical guidance and mentorship to other engineers.

• Conduct code reviews and promote high standards for software quality and maintainability.

• Identify opportunities to improve engineering practices, tooling, architecture, and development efficiency.

• Participate in technical planning, design discussions, backlog refinement, and implementation planning.

• Communicate technical trade-offs and recommendations clearly to engineering, product, implementation, and business stakeholders.

• Take ownership of technical problems from initial discovery through implementation and production delivery.

Required Qualifications

• 10+ years of professional software development experience.

• Demonstrated experience operating at a senior, staff, principal, or architect-level capacity, owning complex technical decisions.

• Strong professional experience with C# and .NET.

• Strong experience developing modern web applications and services using ASP.NET MVC and/or Blazor.

• Proven experience designing and developing scalable SaaS applications or enterprise software.

• Demonstrated experience working with very large datasets, including applications or systems handling tens or hundreds of millions of records.

• Strong understanding of database performance, data access patterns, query optimization, application performance, and scalable system design.

• Experience designing and developing APIs and distributed services.

• Strong understanding of software architecture, design patterns, SOLID principles, and maintainable application design.

• Experience diagnosing complex performance, scalability, and reliability problems.

• Experience with Git and modern software development workflows.

• Experience using AI coding assistants, preferably Claude or comparable agentic coding tools.

• An active personal GitHub profile or public software repository is required. The repository should demonstrate genuine software development experience, technical curiosity, passion for engineering, or meaningful open-source/side-project work. Quality and substance are more important than the number of repositories.

• Strong written and verbal communication skills.

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

Preferred Qualifications

• Experience building tools used by internal implementation, operations, or professional services teams.

• Experience building customer-facing data validation, configuration, onboarding, or implementation tools.

• Experience working with SaaS products that support complex customer implementations.

• Experience designing systems for high-volume data processing or data-intensive applications.

• Experience with cloud platforms, particularly Microsoft Azure.

• Experience with CI/CD and automated deployment practices.

• Experience with containerized or distributed application environments.

• Experience with observability, monitoring, profiling, and production performance analysis.

• Experience establishing or improving AI-assisted engineering workflows.

• Experience using Claude Code, GitHub Copilot, or other AI coding agents in professional development environments.

• Exposure to AI-enabled product features or technologies such as Azure OpenAI, RAG, or LLM-based applications.

What Success Looks Like

Success in this role goes beyond delivering individual features. The engineer will be expected to create tools that produce measurable improvements across the organization.

Within the role, success may include:

• High adoption: Internal implementation teams actively use the tools you build.

• Measurable efficiency gains: Tools reduce manual work, implementation time, or operational overhead.

• Better data quality: Client-facing validation tools help customers identify and resolve data issues earlier in the implementation process.

• Scalable performance: Applications continue to perform effectively as data volumes reach 100+ million records and customer usage grows.

• Customer impact: Tools contribute directly to smoother and faster customer implementations and go-lives.

• Technical excellence: Solutions are maintainable, well-architected, tested, and built to scale.

• Engineering leverage: AI-assisted development and improved engineering practices allow the team to deliver higher-quality solutions faster.

What We’re Looking For

Architectural Thinker: You understand how individual technical decisions affect the broader system and can design solutions with scalability and long-term maintainability in mind.

Hands-On Engineer: You are comfortable working directly in the codebase and solving complex technical problems rather than operating exclusively at a conceptual level.

Scale-Oriented: You have experience building and optimizing systems that work with very large datasets and understand the engineering challenges that emerge at scale.

Tool Builder: You enjoy creating practical tools that make other people’s work faster, easier, and more reliable.

AI-Leveraged: You use AI coding tools as a force multiplier while maintaining complete ownership of the engineering outcome.

Technical Leader: You can make difficult technical decisions, explain tradeoffs, and raise the technical capabilities of the team.

Problem Solver: You enjoy taking ambiguous or complex engineering problems and turning them into practical, scalable solutions.

Engineering-Driven: You maintain a strong personal interest in software development and demonstrate that passion through your work, personal projects, open-source contributions, or GitHub activity.

Customer-Focused: You understand that the ultimate measure of a technical solution is the value it creates for customers and the teams using it.

Join Us and Enjoy These Perks!

Competitive Salary: Earn a USD salary that matches your skills and experience.

Paid Time Off: Generous PTO to support your work-life balance and recharge.

Health Insurance Subsidy: Financial assistance to support your healthcare coverage.

Annual Salary Reviews: Structured annual evaluations to recognize and reward

performance.

Paid Training & Certifications: Continuous support for professional growth and upskilling.

Ready to put your puzzle-solving skills to the test? Join our team today!

LinkedIn: Puzzle

Instagram: @ puzzle.tech

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