Jobs at AgileEngine

Build and maintain scalable backend payment services using Java, Kotlin, and Python. Develop end-to-end payment flows, including charges, refunds, disputes, and webhooks; refactor legacy services; improve testing and APIs; resolve production incidents; and reduce technical debt. Collaborate across engineering and product teams through design, code reviews, and Agile delivery. Document systems and ensure effective handoff to the full-time engineering team.

Develop and maintain Java and Spring Boot microservices for a distributed payments platform. Build payment methods, event-driven workflows, and integrations with external platforms. Improve reliability through observability, resilience patterns, testing, and safe deployments gated by Datadog monitors. Manage transactional consistency, idempotency, JPA entities, schema migrations, and production CI/CD pipelines using GitLab.

Design interaction and visual solutions for complex, multi-step product workflows. Create prototypes, scalable product designs, and engineering-ready specifications while partnering with product managers and engineers through implementation. Collaborate independently across distributed teams and time zones, applying accessibility, responsive design, and error-state considerations.

Lead the architecture of generative AI workflows for cloud configuration and remediation. Build RAG and vector database solutions using LLM APIs to automate Terraform modules, Rego policies, and compliance testing. Oversee AI-enabled cloud security automation, drift detection, discovery, and remediation capabilities. Drive technical strategy, design extensible service architectures, and mentor distributed engineers across global teams.

Execute large-scale data platform migrations to Snowflake, adapting approximately 1,000 datasets and pipelines. Build, test, monitor, and troubleshoot Airflow workflows while supporting migrations from Airflow 2 to 3, Confluent region changes, and Iceberg adoption. Ensure data quality and reliability using Python, advanced SQL, Spark, PySpark, Kafka, Snowflake, and AWS S3. Collaborate with data platform teams on modernization initiatives and meet time-sensitive delivery targets.

Design, develop, and optimize scalable ETL/ELT pipelines using Databricks, PySpark, SQL, GCP, BigQuery, and Delta Lake. Build agentic workflows that automate data validation, troubleshooting, and operational processes. Develop reusable frameworks, implement data quality and monitoring controls, optimize workloads, and support testing, deployment, productionization, and ongoing enhancements across data and AI-enabled solutions.

Lead end-to-end technical delivery across Salesforce, AI agents, integrations, and enterprise workflows. Design scalable solutions, guide Agentforce and Claude implementations, manage project dependencies and risks, review technical designs and code, mentor engineers, and coordinate business, product, architecture, data, and engineering stakeholders. Ensure solutions meet governance, security, reliability, and supportability standards.

Develop backend services primarily with Java and Spring Boot, support Angular frontend development, design RESTful APIs, optimize complex transactional SQL, and work with Oracle or PostgreSQL using JPA/Hibernate. Lead modernization from database-centric systems toward domain-driven architecture, collaborate across squads, and contribute to scalable, high-performance enterprise platforms.

Lead a development squad while remaining hands-on building Java and Spring Boot backend services and Angular frontend features. Design RESTful APIs, modernize database-centric systems using domain-driven design and bounded contexts, and work with Kafka, relational databases, and JPA/Hibernate. Mentor junior engineers, uphold engineering standards, guide agile execution, and advocate for scalable architecture and best practices.

Build and operate cloud infrastructure, CI/CD pipelines, Kubernetes platforms, and observability systems for Data and AI teams. Responsibilities include infrastructure-as-code, cloud security and PCI compliance, incident response, reliability improvements, developer platform tooling, and collaboration across technical teams. The role also establishes DevOps roadmaps, manages production services and on-call operations, and supports secure, scalable environments across AWS, Azure, or GCP.