We are seeking a Senior Golang Engineer to join a growing team focused on building enterprise-scale Generative AI platforms and developer tooling.
This is an opportunity to work at the intersection of cloud-native engineering, distributed systems, and AI, helping deliver the next generation of AI-enabled capabilities within a global financial services environment.
We're looking for strong T-shaped engineers with deep expertise in Golang and broad engineering capability across Kubernetes, platform engineering, DevOps, scalability, and distributed systems. Commercial AI experience is not required, but a genuine interest in Generative AI and emerging technologies is essential.
Essential functions
- Design, develop and operate scalable backend services using Golang.
- Build cloud-native platforms supporting Generative AI and LLM-powered applications.
- Develop reusable libraries, frameworks and internal developer tooling.
- Design and implement distributed systems with a focus on reliability, performance and scalability.
- Collaborate with platform, infrastructure and AI engineering teams.
- Drive engineering best practices, observability, automation and operational excellence.
- Mentor engineers and contribute to technical leadership across the team.
Qualifications
- Strong commercial experience developing software in Golang.
- Deep understanding of distributed systems and backend architecture.
- Strong Kubernetes knowledge and experience running applications in production.
- Experience with microservices, APIs, event-driven architectures and cloud-native technologies.
- Strong understanding of CI/CD, DevOps and platform engineering principles.
- Experience building highly scalable, resilient systems.
- Excellent communication and stakeholder management skills.
Kubernetes
Candidates should possess a strong understanding of Kubernetes concepts equivalent to the core topics covered in Chapters 1–6 of:
Kubernetes in Action
Including:
- Pods, Deployments and ReplicaSets
- Services and Networking
- ConfigMaps and Secrets
- Resource Management
- Health Checks and Application Lifecycle
- Namespaces and Workload Management
- Kubernetes Architecture and Operational Concepts
Would be a plus
Commercial AI experience is not required.
However, candidates should demonstrate:
- Strong interest in Generative AI and LLM technologies.
- Understanding of modern AI tooling and frameworks.
- Experience experimenting with AI-assisted development tools.
- Curiosity around agentic systems, RAG architectures, and enterprise AI adoption.
- Experience with AI/ML platforms or developer productivity tooling.
- AWS, Azure or GCP experience.
- Experience with Kafka, messaging systems or event-driven architectures.
- Financial services or regulated industry experience.
- Platform Engineering or Internal Developer Platform experience.
We offer
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
We cannot offer Sponsorship for this role
About us
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.