Principal GO Developer

Position: Principal GO DeveloperLocation: Denver, CODuration: 1 YearJob DescriptionWe are looking for more experienced (above 12 years) and played lead / architect roles for this position.We are seeking a Senior Engineer to own and evolve a production-critical payment platform responsible for high-volume financial transactions. This role is focused on stability, correctness, and long-term system stewardship, not greenfield development.In addition to strong programming expertise, this role requires experience embedding AI/ML capabilities into enterprise systems and SDLC processes, supporting AI-driven transformation initiatives such as intelligent automation, anomaly detection, and data-driven decisioning within transactional platforms.The ideal candidate has deep experience operating Tier 1 systems where reliability, data integrity, and performance are non-negotiable. They demonstrate strong engineering judgment, maintain a disciplined and low-complexity approach to design, and are capable of driving meaningful improvements independently within an existing distributed system.This role requires a hands-on engineer who can lead through execution, make sound technical decisions under real-world constraints, and contribute to the long-term evolution of a high-value platform, including selective adoption of AI/ML capabilities where they improve system outcomes without compromising stability.Role ContextThe system is a Go-based, microservice-oriented payment platform running in acontainerized environment with a MySQL backend.It supports high-throughput transaction processing and significant annual revenue,making reliability and correctness critical.The platform originated externally and requires thoughtful, incrementalimprovement rather than wholesale redesign.The work involves ongoing evolution of the system, including improving datafidelity, observability, performance, and flexibility while maintaining strictoperational stability.The platform is progressively incorporating AI/ML-driven capabilities, requiringcareful integration into existing system boundaries and SDLC practices.Key ResponsibilitiesOwn and evolve existing Go-based services, making measured, low-risk changesthat improve system capability, reliability, and clarity.Design and implement backend functionality for payment processing, transactionrouting, reconciliation, and financial data movement with a strong focus oncorrectness and auditability.Integrate AI/ML components into the existing architecture (e.g., model inferenceservices, decision engines, data pipelines) while ensuring system stability andauditability.Apply AI/ML Across The SDLC, IncludingIntelligent test generation and validationProduction anomaly detection and incident predictionLog and metric analysis using ML techniquesCode quality and defect prediction toolsCollaborate with data science teams to operationalize ML models (deployment,monitoring, versioning, rollback strategies) within a production-grade environment.Proactively identify system limitations, operational risks, and data gaps, and drivepragmatic solutions with minimal oversight.Evaluate the impact and risk of changes in a high-throughput transactionalenvironment, ensuring safe and controlled rollouts.Improve system observability, data capture, and operational insight to supportboth engineering and business needs, including ML-driven observabilityenhancements.Model and optimize transactional data using relational databases, with carefulattention to consistency, performance, and maintainability.Build and maintain APIs and service interfaces with clear contracts and long-termusability in mind.Contribute to AI transformation initiatives, identifying where AI/ML canmeaningfully enhance system reliability, fraud detection, operational efficiency, ordecision-making.Collaborate with product, architecture, and non-technical stakeholders to ensuresolutions meet business, operational, regulatory, and ethical AI governancerequirements.Provide technical leadership by guiding design decisions, reviewing code, andmentoring engineers while maintaining a focus on simplicity and stability.Own services through their full lifecycle, including design, deployment, monitoring,incident response, and continuous improvement, including ML lifecycle management(MLOps).Mandatory Skills: GO/Golang, MySQL/Oracle/PostgreSQL, AL/ML, AWSOptional Skills: Java, Python, Kubernetes, DockerRequired Qualifications12 plus years of experience in software engineering, demonstrated experiencebuilding and operating production-critical backend systems with meaningful businessor revenue impact.Strong hands-on experience with Go/Golang or Java based technologies in real-world production environments.Experience integrating AI/ML solutions into enterprise systems, includingdeploying, consuming, or operationalizing ML models.Understanding of AI/ML concepts such as supervised/unsupervised learning, modelevaluation, inference pipelines, and data quality considerations.Experience applying AI/ML within SDLC processes (e.g., testing, monitoring,observability, or developer productivity tooling).Deep experience with relational databases (e.g., MySQL, PostgreSQL, Oracle),including schema design, transactional modeling, and performance optimization.Strong understanding of transactional systems, including data integrity,idempotency, reconciliation, auditability, and failure handling.Proven ability to make pragmatic, low-complexity design decisions in distributedsystems.Experience working within and improving existing systems with real-worldconstraints, rather than primarily greenfield environments.Ability to independently identify problems, define solutions, and drive execution tocompletion.Strong communication skills, including the ability to work effectively with bothtechnical and non-technical stakeholders.Preferred QualificationsExperience with payment systems, financial transaction platforms, or other high-integrity data domains.Experience supporting systems with high transaction volume, low latencyrequirements, or strict uptime expectations.Familiarity with MLOps practices, including model deployment, monitoring, driftdetection, and lifecycle management.Experience with real-time or near real-time ML inference systems in productionenvironments.Familiarity with secure data handling, privacy considerations, and ethical AIpractices in regulated environments.Experience with containerized or cloud-based deployment environments (e.g.,Kubernetes, Docker, or similar platforms).Exposure to event-driven or asynchronous processing patterns.Ideal Candidate ProfileOperates as a true owner, not a task executor; identifies issues and drives solutionsindependently.Demonstrates restraint and discipline in system design, avoiding unnecessaryabstraction and complexity.Comfortable working in high-stakes environments where stability and correctnesstake precedence over novelty.Able to apply AI/ML pragmatically, focusing on measurable improvements ratherthan experimentation for its own sake.Calm, methodical, and reliable under production pressure.Able to collaborate effectively with senior peers while mentoring and guidingjunior engineers.Focused on building systems that are understandable, maintainable, resilient, andprogressively intelligent over time.Expectations From This RolePerforms tests in strict compliance with detailed instructions for the following: Ensure that new or revised components or systems perform to expectation. Ensure meeting of standards; including usability, performance, reliability orcompatibility. Document Test results and report defectsTypical Performance Measures Timely completion of all tasks # of test cases/script executed in comparison to the benchmarks # of valid defectsPerformance AreasTest Design, Development, Execution:Execute test cases / scriptsIdentify, log and track defectsRetestLog in productivity dataRequirements ManagementParticipate, Seek Clarification, Understand, ReviewDomain RelevanceTest features and components with good understanding of the business problembeing addressed for the clientManage KnowledgeConsume, ContributeSkill Examples Ability to review user story / requirements to identify ambiguities Ability to design test cases / scripts as per user story / requirements Ability to apply techniques to design efficient test cases / script Ability to set up test data and execute tests Ability to identify anomalies and detail themKnowledge Examples Knowledge of Testing Methodologies Knowledge of Tools Knowledge of Types of testing Knowledge of Testing Processes Knowledge of Testing Standards