Senior Back End Engineer in Mundelein

This is a senior, delivery-focused engagement on a strategic multi-year programme. It suits an engineer who is proactive about building deep domain knowledge, holds themselves to high engineering standards without needing an external quality gate, and is comfortable being challenged by (and challenging) a strong internal engineering team. This is a chance to join a prestigious finance-focused software consulting firm and help modernise systems at the heart of a global Prime Finance business. You’ll build valuable domain knowledge and collaborate with talented engineers., * Understanding of Prime Brokerage, Synthetic (Swap) or Cash Equity operational flows. This is a significant advantage. \n

• Familiarity with corporate actions, regulatory reporting obligations (e.g. 871(m), EMIR, MiFID), and integrating with risk/valuation systems in an equities context. \n

• Strong SQL Server depth: T-SQL, schema design, performance tuning and complex data models in high-transaction environments. \n

• Kafka (or comparable event-streaming platforms) at scale, and MongoDB. \n

• Kubernetes/OpenShift deployment and cloud- operational practices, with observability via OpenTelemetry, ELK and Grafana. \n

• Demonstrated AI-first development experience: agentic coding workflows for legacy analysis, refactoring and test , with a clear-eyed view of where the tools help and where they don’t. \n

• Expert-level Java, with Kotlin experience or a clear appetite for it (enterprise-grade systems, multi-threading, performance). \n

• Practical experience designing and building event-driven systems on message-passing and event-sourcing patterns, including failure handling, ordering guarantees and replay semantics. \n

• Test-Driven Development as a practice, not an aspiration: you own quality end-to-end, you design for testability, and you can demonstrate it through how you approach a problem (this is assessed at interview). \n

• Hands-on experience in or alongside a capital markets trading or post-trade environment: the trade lifecycle, trade booking and position management, and post-trade operations such as cashflow calculation, settlement and wires, client reporting, and accounting principles. You should be able to back this up with concrete examples, not high-level familiarity. \n

• A track record in genuine iterative delivery incl. short feedback loops, trunk-based development, CI/CD, and regular zero-downtime production releases. No waterfall projects labelled as agile. \n

• Proven ability to analyse, refactor and modernise large-scale legacy systems while maintaining stability. \n

• Senior-level autonomy: you contribute to design discussions, push back constructively on technical decisions, and operate with minimal supervision in a complex production environment. \n

• Re-engineering core trading and post-trade systems into event-driven, cloud- services on the JVM (Java and Kotlin). \n

• Modernizing legacy components while keeping a live, financially significant platform stable. \n

• Building the new data and market-expansion platforms that underpin the programme, and the plumbing for advanced client features such as cross-margining and credit financing. \n

• Designing for the realities of event-driven systems: failure handling, ordering guarantees, replay semantics, and data integrity under market pressure. \n

• Practicing TDD and shift-left testing as the default. Local-first testing with containerized dependencies, fast feedback loops, and owning the quality of your deliverables end-to-end rather than handing it to a QA group. \n

• Delivering iteratively: trunk-based development, CI/CD, and frequent (weekly or better) production releases during business hours with no service interruption. \n

• Engaging directly with business stakeholders and upstream/downstream teams to build your own domain knowledge, rather than relying on Business Analysts to hold it for you. \n

• Using AI-assisted and agentic development tooling as a genuine accelerator for analysis of legacy code, test , prototyping and refactoring. \n

\n

\n

Tech stack:

\n \n

• JVM: Java (primary delivery ) and Kotlin. \n

• Messaging and streaming: Kafka, Solace, TIBCO EMS. \n

• Data: SQL Server, MongoDB, S3/object storage. \n

• Cloud and infrastructure: Kubernetes, OpenShift, Docker. \n

• Observability: OpenTelemetry, ELK, Grafana. \n

• Secrets management: HashiCorp Vault, CyberArk. \n

• AI tools: GitHub Copilot, agentic coding tools, recent AI models. \n

\n

\n

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.