AI Architect - Enterprise Platform Capabilities

Essential functions

• Architectural Leadership: Define the overarching architecture and technical strategy for enterprise AI platform capabilities.

• System Design: Design highly scalable AI-native components, including orchestration layers, agent frameworks, RAG (Retrieval-Augmented Generation) architectures, vector search, memory systems, and AI gateways.

• Platform Enablement: Design reusable AI services, SDKs, APIs, and shared capabilities to accelerate AI adoption across various engineering teams.

• LLM Strategy: Lead crucial architectural decisions regarding LLM selection, hosting models, inference patterns, cost optimization, and overall platform scalability.

• Standards & Governance: Establish robust standards and best practices for AI integration, observability, security, privacy, governance, and Responsible AI usage.

• Multi-Agent Systems: Drive the architecture for advanced multi-agent and workflow-based AI ecosystems.

• Cross-Functional Collaboration: Partner closely with engineering teams to guide implementation, and with infrastructure/security teams to define enterprise-ready deployment patterns and compliance controls.

• Innovation & Mentorship: Evaluate emerging AI technologies and frameworks to support long-term platform evolution. Provide technical leadership, mentorship, and support for AI solution discovery, PoCs, and productionization strategies.

Qualifications

• Enterprise Architecture: Proven experience designing distributed systems, complex enterprise platforms, and modern backend architectures.

• Programming Mastery: Strong, hands-on coding experience, primarily in Python.

• Deep AI/LLM Expertise: Profound understanding of LLM ecosystems, generative AI architectures, and AI orchestration patterns.

• Data & Search: Hands-on experience designing RAG systems, semantic search, embeddings pipelines, and vector database architectures.

• Cloud Infrastructure: Extensive experience with cloud-native architectures on AWS, Azure, or GCP. Solid understanding of AI infrastructure, model serving, inference optimization, scalability, and reliability.

• Integration & Security: Experience defining API strategies and reusable engineering standards. Strong knowledge of enterprise security, privacy, and Responsible AI principles.

• Exceptional Communication: The ability to seamlessly translate complex architectural concepts to both deeply technical engineering teams and C-level executive stakeholders.

Would be a plus

• AI Frameworks: Hands-on experience with tools like LangChain, Semantic Kernel, AutoGen, CrewAI, LlamaIndex, or similar orchestration frameworks.

• DevOps & Automation: Experience with Kubernetes, Docker, CI/CD pipelines, and infrastructure automation.

• MLOps / LLMOps: Knowledge of modern MLOps practices, AI observability, evaluation frameworks, guardrails, and model monitoring.

• Advanced Architectures: Experience designing multi-tenant enterprise platforms, event-driven architectures, streaming systems, and workflow orchestration.

• Transformation: Previous experience supporting large-scale AI transformation initiatives within complex enterprise environments.
  
  Why Join Us? You will be at the forefront of the AI revolution, building the foundational systems that will power the next generation of enterprise products. You will have a high level of decision-making authority, the opportunity to mentor top-tier engineering talent, and the chance to work with the most advanced technologies in the market today.

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.