TechOps - DE - AI - Senior - GDSN02
Ernst and Young1 day ago
Bengaluru, IndiaSenior
Responsibilities
- Design, develop, deploy, and operationalize Agentic AI solutions using LLMs, multi-agent architectures, retrieval systems, and orchestration frameworks.
- Architect autonomous workflows and intelligent agents that reason, plan, make decisions, and execute tasks across enterprise systems.
- Integrate LLMs, NLP, computer vision, and AI/ML services into enterprise applications through APIs, SDKs, and cloud-native services.
- Build custom Python applications, services, automation logic, and reusable accelerators for end-to-end workflow automation.
- Define agent behaviors, tool integrations, guardrails, evaluation frameworks, and success metrics with cross-functional teams.
- Monitor, troubleshoot, maintain, and optimize AI agents and automated workflows for reliability, scalability, security, and performance.
- Establish technical standards, reusable components, reference architectures, documentation, runbooks, and deployment guidelines.
- Evaluate emerging AI technologies and orchestration platforms and recommend solutions that improve business value and operational efficiency.
- Provide technical leadership and mentorship, participate in architecture and code reviews, and promote engineering best practices.
- Support AI and automation business development through solution design, proposals, workshops, demonstrations, and technical presentations.
- Ensure solutions comply with security, governance, risk management, privacy, regulatory, and Responsible AI requirements.
- Coordinate resource planning, effort estimation, prioritization, stakeholder management, and delivery of AI initiatives.
Requirements
- Bachelor’s or master’s degree in computer science, engineering, or a related field.
- At least 5 years of professional software engineering experience.
- At least 2–3 years of hands-on experience designing, developing, and deploying Generative AI, Agentic AI, intelligent automation, or AI-powered enterprise solutions.
- Proven experience with LLMs, RAG, prompt engineering, agent orchestration frameworks, and AI-powered workflows.
- Hands-on experience with AI/ML frameworks, NLP technologies, vector databases, semantic search, and enterprise knowledge retrieval systems.
- Strong Python programming expertise and working knowledge of JavaScript or TypeScript, including experience developing APIs, automation services, and enterprise integrations.
- Experience with cloud platforms and AI or machine learning services on Microsoft Azure, AWS, or Google Cloud.
- Understanding of model evaluation, monitoring, observability, AIOps, MLOps, LLMOps, and governance practices for production AI systems.
- Experience with multi-agent systems, MCP, AI copilots, and enterprise AI platforms.
- Knowledge of embeddings, knowledge graphs, and enterprise data integration patterns is highly desirable.
- Experience building AI, generative AI, automation solutions, accelerators, and reusable frameworks in managed services or large-scale enterprise environments is preferred.
- Strong communication, presentation, stakeholder collaboration, problem-solving, mentoring, and technical leadership skills.
- Ability to balance innovation with security, privacy, compliance, Responsible AI, and enterprise governance requirements.
Benefits
- Flexible work environment with globally connected, distributed, hybrid teams.
- Professional development through skill building, leadership opportunities, mentorship, and continuous learning.
- Diverse, equitable, and inclusive workplace culture.
- Health and wellness packages, rewards, and learning opportunities.
Tech Stack
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