Tech S And T-Technical Architect-Manager-GDSN04
Ernst and Young12 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Own backend and agentic platform architecture for Python-led services, APIs, automation utilities, AI/LLM integrations, multi-agent workflows, and enterprise integration layers.
- Define architecture principles, reference patterns, coding standards, and reusable engineering assets.
- Translate functional and non-functional requirements into decisions covering scalability, security, performance, reliability, and maintainability.
- Lead technical design reviews, code reviews, dependency assessments, and production-readiness checks.
- Guide engineers on Python services, Java integration, API contracts, database access, error management, and automated testing.
- Partner with product owners, architects, DevOps teams, and security stakeholders on technology choices and delivery priorities.
- Drive CI/CD, environment readiness, observability, logging, monitoring, vulnerability remediation, and release governance.
- Identify delivery risks, remove technical blockers, manage dependencies, and ensure teams have appropriate tools and standards.
- Mentor senior developers, support capability building, and promote documentation and reusable engineering practices.
- Contribute to estimation, sprint planning, backlog refinement, stakeholder communication, and technical decision-making.
Requirements
- Strong hands-on Python and Java programming experience for backend services, automation, scripting, and enterprise integration.
- Experience designing APIs, microservices, event/message-based integrations, and service-to-service communication patterns.
- Strong understanding of SQL/relational databases, data modeling, query optimization, transaction handling, and application-service integration.
- Experience with CI/CD, Git-based version control, automated testing, code quality gates, release management, and DevOps practices.
- Ability to define architecture decisions, document trade-offs, and govern implementation quality across multiple engineers.
- Security-aware experience covering secure coding, secrets handling, dependency hygiene, vulnerability remediation, and compliance-aware delivery.
- Mandatory experience with AI engineering concepts, LLM-based solution design, prompt/orchestration patterns, and enterprise AI integration.
- Hands-on knowledge of agentic frameworks and platforms including Microsoft Agent Framework, Azure AI Foundry, Foundry SDK, OpenAI Agents SDK, Semantic Kernel, AutoGen, LangChain, LangGraph, CrewAI, and LlamaIndex Workflows.
- Understanding of autonomous workflows, tool/function calling, MCP-based tool integration, multi-agent orchestration, human-in-the-loop patterns, memory, planning, and AI-enabled SDLC acceleration.
- Ability to evaluate agentic frameworks based on complexity, orchestration, model compatibility, tool ecosystem, MCP/A2A readiness, deployment, governance, observability, security, and support requirements.
- Working understanding of Azure OpenAI, OpenAI APIs, Microsoft Foundry model endpoints, embeddings, retrieval, file search, code interpreter, web search, memory, safety controls, and evaluation workflows.
- Understanding of robotics, automation platforms, robotic process automation, or robotics-integrated digital solutions.
- Strong communication, stakeholder management, coaching, and team leadership skills.
- Preferred experience with cloud-native architecture, containers, Kubernetes, serverless patterns, platform engineering, or infrastructure automation.
- Preferred exposure to AI-assisted engineering, agentic workflows, engineering productivity tooling, regulated or security-sensitive domains, and distributed technical delivery.
Benefits
- Flexible work environment with globally connected teams.
- Health and wellness packages, rewards, and learning opportunities.
- Professional development, mentorship, skill building, and opportunities to take on leadership roles.
- Inclusive culture focused on diversity, equity, inclusion, belonging, and employee accommodations.
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