Codeminders/Tristero Consulting

• Design and build scalable backend services. • Improve developer productivity. • Lead technical initiatives across the engineering organization.

• Develop modern web applications using ReactJS and TypeScript. • Design and implement reusable UI components and scalable frontend architecture. • Build and maintain state management solutions and API integrations. • Deliver responsive, accessible, and high-quality user interfaces. • Collaborate closely with design and product teams to translate requirements into intuitive user experiences. • Ensure frontend applications meet high standards of performance, maintainability, and usability. • Architect and build backend services using Python (FastAPI preferred) or Java (Spring Boot / Quarkus). • Design and implement scalable RESTful and GraphQL APIs with a focus on performance, security, and maintainability. • Build asynchronous processing pipelines using technologies such as Celery, RabbitMQ, Redis, or similar message brokers. • Design and optimize database schemas using PostgreSQL, MySQL, or NoSQL databases. • Implement caching strategies to improve system performance and reduce latency. • Optimize backend services for high throughput, scalability, and reliability.

• Design, execute, and maintain manual and automated test cases. • Perform API testing and API test automation. • Perform UI testing and UI test automation for web applications. • Identify, document, and track software defects through resolution. • Collaborate closely with developers, product managers, and stakeholders to ensure product quality. • Participate in requirement analysis, test planning, and release validation. • Utilize AI-powered tools to improve test coverage, productivity, and overall QA processes. • Work independently and take ownership of testing activities throughout the software development lifecycle.

• Design, build, and operate scalable backend systems and cloud-native infrastructure. • Deploy, manage, and optimize applications on AWS (EC2, ECS/EKS, Lambda, S3, RDS, CloudWatch, IAM, and related services). • Design and maintain CI/CD pipelines and automated testing workflows. • Use Docker and Kubernetes for containerization and orchestration of microservices. • Implement observability solutions, including logging, monitoring, metrics, and distributed tracing. • Ensure infrastructure reliability, scalability, and operational efficiency. • Architect and build backend services using Python (FastAPI preferred) or Java (Spring Boot / Quarkus). • Design and implement scalable RESTful and GraphQL APIs. • Develop asynchronous processing pipelines using technologies such as Celery, RabbitMQ, Redis, or similar. • Design and optimize database schemas using PostgreSQL, MySQL, or NoSQL databases. • Implement caching strategies to ensure high performance and low latency. • Optimize backend systems for high throughput, resilience, and reliability.

• Validate data accuracy, completeness, and consistency across multiple systems. • Perform data quality testing for ETL/ELT pipelines and reporting solutions. • Write complex SQL queries for data validation and reconciliation. • Analyze and troubleshoot data discrepancies between source and target systems. • Review and debug Python-based data pipeline code. • Collaborate with engineers and stakeholders to maintain data integrity.

• Develop modern web applications using ReactJS and TypeScript. • Design and implement reusable UI components and scalable frontend architecture. • Build and maintain state management solutions and API integrations. • Create responsive, accessible, and user-friendly interfaces across devices and browsers. • Collaborate with designers and product teams to translate requirements into intuitive user experiences. • Ensure high standards of performance, maintainability, and code quality in frontend applications. • Deploy, configure, and manage applications on AWS (EC2, ECS/EKS, Lambda, S3, RDS, CloudWatch, IAM, and related services). • Design and maintain CI/CD pipelines for automated testing and deployments. • Work with Docker and Kubernetes for containerization and orchestration of services. • Implement observability practices, including logging, monitoring, and distributed tracing. • Support infrastructure provisioning and environment automation.

• Design, develop, and maintain scalable full-stack applications. • Build robust backend services using Python and FastAPI. • Develop modern frontend applications using ReactJS and TypeScript. • Design and implement RESTful and GraphQL APIs. • Build and maintain asynchronous processing systems using Celery or similar technologies. • Architect and implement cloud-native solutions on AWS. • Design scalable microservices and distributed systems. • Participate in system architecture, code reviews, and technical decision-making. • Implement CI/CD pipelines and DevOps best practices. • Ensure system reliability, performance, security, and maintainability. • Collaborate with product managers, designers, and engineering teams to deliver business value. • Leverage AI technologies and integrate AI capabilities into products where appropriate.

• Build Ray-based distributed task graphs for inference, training, RAG, vector search, document retrieval, video, and compound workloads. • Develop Ray head and worker deployment patterns on Kubernetes. • Create per-hardware workload drivers for GPU inference, vector search, storage retrieval, video acceleration, and edge inference. • Implement model-locality and cache-awareness logic so workloads run near the right model or data. • Ensure integration between scheduling decisions, capacity state, SLA rules, billing events, and observability traces. • Conduct end-to-end workload tests for compound RAG and multi-plane AI jobs.

• Build Kong or OpenResty plugin logic in Lua • Perform request classification for inference, training, RAG, video, compute, and edge inference APIs • Handle JWT/OIDC tenant identity extraction and validation • Implement Redis-backed quota checks, concurrency caps, routing lookups, and request metadata • Manage low-latency connection pooling and timeout behavior • Ensure gateway observability: p50/p95/p99 latency, errors, Redis latency, routing decisions, and tenant-level behavior • Conduct load tests and failure tests for various scenarios including Redis outage, malformed tokens, quota exhaustion, and routing-table updates

• Go services for SLA enforcement, capacity management, compliance routing, identity routing, auth, and billing integration • High-concurrency routing and policy logic for customer AI workloads • Integrations with Kubernetes capacity APIs, identity-routing systems, Redis, billing systems, and observability systems • Redis-backed quota, rate-limit, routing-cache, and failover behavior • Tenant-isolation and compliance-enforcement logic that works under real load • Failure-mode tests for degraded dependencies, Redis failover, and inconsistent capacity state