Jobs at Sparq

Leads AI-focused technical pre-sales, client discovery, solution architecture, proposals, commercial modeling, and executive engagement. Designs scalable AI and cloud architectures across AWS, Azure, GCP, Snowflake, and Databricks; operationalizes LLMs and agentic workflows; develops AI offerings and thought leadership; and supports delivery transitions, governance, and value realization. Mentors consulting teams and shapes complex enterprise AI engagements, with travel up to 40%.

Designs and maintains Azure cloud infrastructure, reusable Terraform IaC modules, no-code deployment packages, and CI/CD pipelines. Develops automated infrastructure tests with Go and TerraTest, troubleshoots deployments, and improves automation reliability. Collaborates with architects, analysts, and engineering teams to implement standardized solutions. Uses AI tools such as Claude, documents work in JIRA and Confluence, supports client goals, and mentors colleagues.

Designs and automates performance testing for mobile applications using load-testing tools, cloud infrastructure, containers, and CI/CD pipelines. Develops ramped-load, capacity, and spike scenarios; schedules recurring tests; configures alerts and pass/fail thresholds; analyzes results through observability tools; and identifies performance bottlenecks. The role also manages authentication, documentation, client collaboration, environment readiness, project deliverables, and knowledge transfer while mentoring teammates and promoting AI adoption.

Designs, develops, and maintains automated testing solutions across non-production and production environments. Integrates automated workflows with Jenkins and CI/CD pipelines, performs API testing with Postman Enterprise, validates databases using SQL, and supports JSON/XML-based orchestration. Collaborates with Java and C development teams to investigate defects and improve test coverage. Provides technical leadership, mentors colleagues, promotes automation best practices, and helps integrate AI tools into daily engineering workflows.

Designs, builds, deploys, evaluates, and optimizes production AI systems, including RAG pipelines, agentic workflows, and model integrations. Uses Python and cloud platforms to deliver scalable solutions, establishes quality and monitoring frameworks, addresses responsible AI and security concerns, and manages cost-performance tradeoffs. Serves as a senior technical client advisor, supports discovery and presales, mentors engineers, researches emerging AI technologies, and develops reusable accelerators.

Lead development of production-grade Flutter and Dart mobile applications, including shared offline capabilities, local persistence, background synchronization, conflict resolution, data-age safeguards, and reliability testing. Provide technical leadership through code reviews, troubleshooting, mentoring, and collaboration while leveraging AI tools such as Claude and Claude Code. Ensure performance and compatibility across devices and operating systems and oversee delivery of scalable, maintainable mobile solutions.

Designs and supports enterprise DevOps tooling, including Jenkins, Bitbucket, and JFrog Artifactory. Responsibilities include disaster recovery, repository and artifact governance, open-source dependency security, DevSecOps controls, technical documentation, and platform migration support. The role also promotes AI tool adoption, provides project oversight, mentors colleagues, and works collaboratively with clients and engineering teams.

Partners with DevTools engineers and stakeholders to capture requirements, document CI/CD recovery and repository governance processes, track scope and dependencies, and support GitHub migration readiness. The role facilitates technical alignment, maintains project documentation, oversees deliverables, and promotes AI tool adoption. Central Time Zone availability is required.