Forward Deployed Engineer

Essential functions

• Enterprise Integration & Deployment: Architect, deploy, and maintain the orchestration platform in complex customer environments (AWS, GCP, Azure, Kubernetes, on-premises, and air-gapped networks), owning each rollout through to stable production.

• Security & Governance: Configure SSO/OAuth (SAML/OIDC), integrate identity providers, set up API proxies, and enforce SOC2, HIPAA, and ISO compliance policies for AI traffic.

• Model & Agent Orchestration: Integrate external and internal LLM providers (Amazon Bedrock, Azure OpenAI, Ollama, custom enterprise endpoints) and configure platform CLI tools and IDE extensions for end users.

• Context & CI/CD Pipelines: Embed semantic code-indexing engines into client CI/CD pipelines, so AI agents get real-time context from large-scale codebases, API schemas, and internal documentation.

• Product Engineering Feedback Loop: Act as the technical voice of the client to core R&D and Product teams, turning edge cases, enterprise security demands, and custom integrations into core product features.

• Enablement & Best Practices: Partner with customer DevEx leaders and Tech Leads to define best practices for AI agent governance, token usage monitoring, and developer productivity metrics.

Qualifications

• 4+ years of professional software development experience in Kotlin, Java, Go, Python, or TypeScript.

• Cloud Native & DevOps: Strong background in Docker, Kubernetes, Helm, and Terraform, and in managing infrastructure on AWS, GCP, or Azure, or on private clouds such as OpenShift.

• Enterprise Security & Networking: Hands-on experience with TLS/mTLS, reverse proxies, API gateways, enterprise auth (SAML, OIDC), and air-gapped security requirements.

• Developer Ecosystems: Deep understanding of modern IDE setups, Git, GitHub/GitLab, CI/CD runners (GitHub Actions, GitLab CI), and CLI workflows.

• AI/LLM Infrastructure: Experience working with LLM APIs, AI proxies, agent protocols such as Model Context Protocol (MCP), or local LLM runtimes.

• Customer-Facing Technical Presence: Proven ability to drive technical discussions with CISOs, Enterprise Architects, and Principal Engineers.

Would be a plus

• IDE & Tooling Plugins: Experience developing plugins for modern IDE ecosystems or developer tools.

• Field Engineering Background: Previous work as a Forward Deployed Engineer, Solutions Architect, or DevEx Consultant in AI, developer tools, or data infrastructure.

• Semantic Search at Scale: Practical knowledge of vector databases, RAG pipelines, or semantic code search at scale.

• Travel Flexibility: Willingness to travel to client sites as required (typically up to 25%).

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

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.