You also bring practical experience with agent-based AI development workflows beyond code completion. You can work with specialized agents, maintain their instructions and skills, and connect them to development tools while retaining human accountability for decisions and quality. You communicate clearly, welcome technical debate, and support the team’s agreed direction once a decision is made.
Who You Are
An accountable engineer who takes ownership of services from design through production.
A clear written communicator who explains designs, supports recommendations with evidence, and documents decisions effectively.
A collaborative technical peer who welcomes open debate and commits to the team’s agreed direction.
A pragmatic problem-solver who improves working systems incrementally rather than defaulting to rewrites.
A supportive reviewer and mentor who helps other engineers develop sound integration and testing practices.
A thoughtful user of AI who understands its capabilities and limitations and retains responsibility for engineering quality.
A continuous learner who keeps technical knowledge, documentation, and development practices aligned with an evolving platform.
What You’ll Be Doing
Owning and evolving the event orchestration service, including scheduled jobs, chained events, retries, and variable extraction, with a focus on reliability, observability, and maintainability.
Designing and delivering integrations with internal and third-party systems through REST APIs, databases, and data warehouses, incorporating idempotent synchronization, failure handling, and reconciliation.
Defining platform patterns alongside the lead engineer for API design, caching, authentication and authorization, and service-to-service communication, and documenting decisions through Architecture Decision Records.
Establishing testing patterns across services, including unit, integration, and contract tests, mocking of external systems, and coverage gates in CI, while supporting adoption by service owners.
Working within and improving an AI-agent development workflow spanning requirements analysis, development, testing, merge request review, and ticket management, with defined quality gates.
Keeping the agents, instructions, skills, and knowledge base for your areas accurate and aligned with platform changes.
Acting as the primary technical reviewer for your areas and mentoring less experienced engineers, particularly in integration design and implementation.
Managing production health, performance, and incident follow-up for your services within a Kubernetes-based environment.
The Impact You Will Have
Strengthen the reliability of the Operations Project Management platform through dependable event orchestration and resilient integrations.
Improve data consistency across connected business systems, reducing synchronization failures and enabling effective reconciliation.
Make services easier to operate and troubleshoot through clear observability, documentation, and actionable incident follow-up.
Increase confidence in platform changes through consistent testing practices and automated quality gates.
Improve architectural consistency across microservices through shared patterns and documented technical decisions.
Enable effective use of AI agents throughout the development lifecycle while maintaining engineering accountability for decisions and delivery quality.
Build the team’s integration expertise through technical reviews, mentoring, and knowledge sharing.
Support sustainable platform evolution through incremental improvements that preserve operational continuity.
What You’ll Need
Degree or Master in Informatic Engineering or related.
At least 7 years of backend engineering experience, with a strong track record in system integrations, including APIs, ETL and synchronization pipelines, and data consistency across systems.
Hands-on experience with event-driven or job-orchestration systems, including schedulers, workflow engines, queues, retries, and their failure modes.
Strong Python development skills.
Good knowledge of relational databases, such as MySQL, and SQL, including data modeling, query performance, and database migrations.
Experience designing REST APIs, caching strategies, and authentication and authorization mechanisms, including OAuth2, tokens, and service accounts.
Hands-on experience with agent-based AI development workflows beyond code completion, using role-based agents in tools such as GitHub Copilot, Claude Code, or similar.
Experience writing or maintaining agent instructions and skills, and connecting agents to tools through MCP or similar mechanisms.
A disciplined approach to AI configuration, including version control, review, ongoing maintenance, and recognition of where human validation is required.
Demonstrated experience introducing or improving team testing practices, rather than solely writing tests.
Practical experience with containers, Kubernetes, and GitLab CI or comparable CI/CD tooling.
Preferred experience
Django and Django REST Framework.
Snowflake, Microsoft Fabric, or other cloud data platforms.
Integrations with enterprise tools such as Jira, SharePoint/Microsoft Graph, or project portfolio management systems.
Using MCP servers to connect AI agents to issue tracking, documentation, source control, and the wider development ecosystem.
GitOps practices and tooling, such as FluxCD or ArgoCD, and secrets management.
Experience as a technical lead or architect within a small engineering team.
Who You Are
An accountable engineer who takes ownership of services from design through production.
A clear written communicator who explains designs, supports recommendations with evidence, and documents decisions effectively.
A collaborative technical peer who welcomes open debate and commits to the team’s agreed direction.
A pragmatic problem-solver who improves working systems incrementally rather than defaulting to rewrites.
A supportive reviewer and mentor who helps other engineers develop sound integration and testing practices.
A thoughtful user of AI who understands its capabilities and limitations and retains responsibility for engineering quality.
A continuous learner who keeps technical knowledge, documentation, and development practices aligned with an evolving platform.
The Team You’ll Be A Part Of
You will join the engineering team that builds and operates Synopsys’ Operations Project Management platform. Built as a set of Python/Django microservices, the platform connects to key business systems across project portfolio management, data warehousing, issue tracking, and document management. The team owns the full lifecycle, from design and development through production operations on Kubernetes.
Working as a technical peer to the lead engineer, you will help shape a high-ownership environment where architectural decisions are documented, technical ideas are debated openly, and improvements are delivered incrementally. Specialized AI agents support and coordinate work throughout the development workflow, while engineers remain accountable for decisions, quality, and production outcomes.
Rewards and Benefits
We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings.
