Platform Engineer

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & Dev Ops, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our Fin Labs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more.

Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 17,000+, and has 58 offices in 22 countries within key global markets.

We are seeking a hands-on Platform Engineer with full-stack development and AI engineering expertise.

The role focuses on building secure, scalable, and resilient platforms for critical financial applications.

The engineer will own end-to-end solutions, from design and coding through deployment, observability, and production support.

The role involves close collaboration with platform, application, SRE, cybersecurity, infrastructure, and production teams.

The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Alpharetta, GA is $105k - $115k/year & benefits (see below).

• Design, develop, test, and operate production-grade APIs, backend services, web applications, and developer platforms.
• Build self-service portals, platform catalogs, reusable components, integrations, and automation across enterprise systems.
• Deliver secure, maintainable, well-tested code and own solutions across the full SDLC, including CI/CD, deployment, rollback, and documentation.
• Develop AI agents and RAG-based workflows for architecture analysis, knowledge discovery, standards validation, evidence collection, and remediation planning.
• Integrate AI solutions with enterprise APIs and tools using secure, controlled interfaces such as MCP, with appropriate evaluation and governance frameworks.
• Engineer resilient, scalable systems using high-availability, fault-tolerance, disaster-recovery, observability, and performance-testing practices.
• Translate architecture standards into reusable libraries, reference implementations, automated checks, platform guidance, and engineering guardrails.
• Identify design deviations and operational risks, support remediation tracking, and promote best practices through documentation, mentoring, and engineering forums.

• Strong hands-on software development experience using Java, Python, C#/.NET, or comparable backend technologies.
• Experience developing user interfaces with React, Angular, Type Script, or an equivalent modern framework.
• Demonstrated ownership of production applications or platform services, from design through operational support.
• Experience designing APIs, distributed systems, asynchronous integrations, and relational or No
  
  SQL data access.
• Practical experience developing LLM-enabled applications, AI agents, retrieval workflows, or AI-powered automation.
• Experience with containers, Kubernetes or equivalent platforms, CI/CD, and infrastructure/configuration as code.
• Strong understanding of authentication, authorization, secrets management, secure coding, and data protection.
• Ability to diagnose application, database, network, and dependency-related performance or reliability issues.
• Strong collaboration skills and the ability to explain technical decisions and trade-offs to diverse stakeholders.

• Experience with Wealth Management, banking, trading, or other high-availability transaction-processing systems.
• Familiarity with API gateways such as Apigee, messaging platforms such as Kafka or MQ, and distributed caching.
• Experience with MCP integrations, agent orchestration, vector search, AI evaluation, and production AI monitoring.
• Knowledge of multi-data-center architecture, disaster recovery, SLOs, and resilience testing.
• Experience building internal developer platforms, service catalogs, policy-as-code, or automated architecture-governance capabilities.

• A highly competitive compensation and…