ai engineer in payment security

Grid Dynamics provides technology consulting, platform and product engineering, AI, and advanced analytics services. It helps enterprise companies solve complex technology challenges and achieve business outcomes during digital transformation.

• Design, build, and maintain the platform’s core model runtime, including backends, per-stage model assignment, prompt caching, and context window token budgeting;
• Implement safe, cost-effective, diff-only repository scanning using tree-sitter call graphs, resilient fingerprinting, and concurrency leases;
• Build dynamic, permission-aware RAG and retrieval capabilities over enterprise knowledge bases and deliver versioned detection lenses and rule packs;
• Develop integrations and connectors across GitHub, GitLab, Jira, and CI/CD pipelines, automating draft PR generation, issue tracking, and short-lived credential management;
• Establish system observability with per-stage tracing, token and cost tracking, and SOC logging;
• Enforce release hygiene through containerization, lockfiles, and signed builds;
• Integrate external security scanners into unified harness findings and build reviewer feedback loops for precision tracking and GRC/ASPM exports;
• Execute secure sandboxing, runtime checkpointing, and throwaway worktree mitigations for automated remediation loops.

• 5+ Years of commercial software, ML platform, or infrastructure engineering experience building enterprise-grade systems;
• Strong hands-on proficiency in Python, Go, or Rust;
• Deep expertise in LLM infrastructure, model runtimes, prompt engineering, and RAG architectures;
• Hands-on experience with code parsing tools such as Tree-sitter for AST analysis, boundary chunking, and dependency graph extraction;
• Experience automating developer workflows across GitHub, GitLab, Jira, and CI/CD systems using ephemeral authentication;
• Strong expertise in release engineering and platform security, including containerization, signed builds, Infrastructure as Code, and secure-by-design practices;
• Background in system observability, including tracing, logging, and token and cost metrics tracking across complex platform pipelines;
• Nice to have: experience integrating external security scanners or vulnerability intelligence feeds, knowledge of payment processing, financial services, or highly regulated enterprise environments, experience with GRC and ASPM tool ecosystems, background in deterministic evaluation frameworks, baseline measurement, and regression testing for AI loops.

• Competitive salary;
• Flexible schedule;
• Benefits package including medical insurance and sports;
• Corporate social events;
• Professional development opportunities;
• Well-equipped office.