Enterprise Architect

Job Title: Enterprise Architect – AI & Intelligent Systems

Location: Any GlobalLogic India office locations

Experience: 12–18+ years overall, with 5+ years in AI/ML architecture

Role Summary

We're looking for an Enterprise Architect who can design and govern AI-driven architectures across the full spectrum — from traditional structured data platforms to unstructured data pipelines, agentic AI systems, and emerging physical AI (robotics/embodied AI) use cases. This person will act as the technical bridge between business strategy, data architecture, and next-generation AI deployment, ensuring solutions are scalable, secure, and interoperable across the enterprise.

Key Responsibilities

\n
• Define and own the enterprise AI architecture strategy, covering data (structured/unstructured), model layers, and agentic orchestration
\n
• Architect solutions integrating structured data (relational, data warehouses) and unstructured data (documents, images, video, sensor/IoT streams) into unified AI-ready platforms
\n
• Design agentic AI systems — multi-agent orchestration, tool-use frameworks, propose/review governance models, and human-in-the-loop controls
\n
• Provide architectural guidance on physical AI / embodied AI initiatives (robotics, digital twins, sensor fusion, edge inference) where AI models interact with physical systems
\n
• Establish reference architectures, patterns, and reusable frameworks (RAG pipelines, vector stores, agent skill definitions, model routing/tiering)
\n
• Evaluate and select AI toolchains (LLM providers, orchestration frameworks like LangGraph/AutoGen, MCP-based integrations, vector databases)
\n
• Define governance for AI safety, model access tiers, data security, and compliance (especially around LLM API access, IP, and sandboxing)
\n
• Partner with client stakeholders and delivery teams to translate business requirements into scoped technical solutions and SOWs
\n
• Guide integration of AI into existing enterprise systems (ERP, asset management, monitoring platforms) without disrupting core operations
\n
• Mentor engineering and delivery teams on AI/ML best practices and architectural standards
\n
• Stay current on emerging AI trends (agentic frameworks, small/edge models, robotics AI stacks) and translate them into actionable enterprise roadmaps
\n

Required Skills & Experience

\n
• Strong background in Enterprise Architecture frameworks (TOGAF, Zachman, or equivalent)
\n
• Hands-on experience with structured data platforms (SQL, data warehousing, ETL/ELT) and unstructured data processing (NLP, computer vision, document AI)
\n
• Practical knowledge of agentic AI architectures — multi-agent systems, tool/function calling, orchestration frameworks, memory/context management
\n
• Familiarity with physical AI / embodied AI concepts — robotics middleware (ROS), sensor fusion, edge AI inference, digital twins, or industrial IoT integration
\n
• Experience with LLM ecosystems (OpenAI, Anthropic, open-source models), vector databases (Pinecone, Weaviate, pgvector), and RAG architecture
\n
• Cloud architecture expertise (AWS/Azure/GCP) with AI/ML services (SageMaker, Azure AI, Vertex AI)
\n
• Understanding of AI governance, model risk management, and responsible AI principles
\n
• Experience architecting solutions with security/compliance constraints (data residency, access control, sandboxed execution environments)
\n
• Strong stakeholder management — able to translate architecture into business language for CXO-level audiences
\n
• Prior experience with pre-sales/solutioning, scoping, or SOW development is a plus
\n

Preferred / Nice-to-Have

\n
• Exposure to industrial/OT environments (manufacturing, energy, utilities) where physical AI is being piloted
\n
• Experience with GitHub Copilot Agent Mode, Copilot CLI, or similar propose-only agent governance models
\n
• Certifications: TOGAF, AWS/Azure AI certifications, or relevant AI/ML credentials
\n
• Experience in domains like asset management, predictive maintenance, or diagnostics (e.g., DGA/transformer monitoring) is a strong plus
\n

Soft Skills

\n
• Systems thinker with ability to balance innovation against enterprise risk/governance
\n
• Strong communicator across technical and business audiences
\n
• Comfortable operating in ambiguity — many AI use cases (like physical AI) are still maturing
\n

note : Please apply only one month notice period candidates as this position is super urgent