- Location
- Noida, UP,IN, IN
- Type
- Full-time
- Department
- Engineering
- Seniority
- Lead
- Experience
- 10+ years
- Source
- Eightfold
Description
- Define and evolve the architecture for LLM-powered AI agents, intelligent assistants, and shared agentic capabilities across UKG products, including HCM, WFM, HRSD, and Genesis. - Drive architectural decisions across agent orchestration, multi-agent workflows, APIs, reusable frameworks, tool and function calling, enterprise data integration, RAG, memory, model selection, and integration patterns. - Design extensible and reusable agentic capabilities that can be adopted across multiple UKG products while accommodating product-specific requirements and business contexts. - Ensure AI systems are designed for high availability, scalability, accuracy, security, privacy, observability, auditability, responsible AI, and regulatory compliance. - Establish robust approaches for AI-agent evaluation, hallucination detection, guardrails, human-in-the-loop controls, prompt and model versioning, and continuous quality improvement. - Lead architecture and design reviews, setting standards for agent design, code quality, model and response quality, operational readiness, and cross-product adoption. - Provide technical direction and mentorship to engineering teams while influencing the broader agentic AI strategy and engineering practices across UKG. - 10+ years of professional software engineering experience - Deep experience designing and building scalable distributed systems, enterprise platforms, APIs, and cloud- native services. - Hands- on experience designing, building, and productionizing LLM- powered applications, AI agents, intelligent assistants, or other generative AI solutions. - Strong understanding of agentic AI concepts and patterns, including agent orchestration, tool and function calling, RAG, memory, prompt engineering, model selection, evaluation, guardrails, and human-in-the-loop workflows. - Experience integrating AI systems with enterprise applications, APIs, data sources, identity and access controls, and business workflows. - Experience building and operating secure, observable, resilient, and business- critical AI capabilities consumed across multiple products or engineering teams. - Understanding of responsible AI practices, including data privacy, security, explainability, auditability, bias mitigation, hallucination management, and regulatory compliance. - Track record of influencing technical direction across multiple teams or organizations, establishing architectural standards, and driving adoption of shared frameworks and engineering practices. - Strong problem-solving skills, with the ability to translate ambiguous product or business requirements into clear, extensible technical designs. - Proven ability to lead highly complex, cross- functional initiatives involving engineering, product management, architecture, AI/ML, data, security, and compliance teams. - Demonstrated ability to mentor senior engineers, raise engineering standards, and deliver AI capabilities with significant customer and business impact. - Experience with LLM and agentic AI frameworks, model providers, vector databases, semantic search, knowledge graphs, or enterprise RAG architectures. - Familiarity with advanced agentic patterns such as multi-agent collaboration, planning and reasoning, dynamic tool selection, agent memory, and autonomous workflow execution. - Experience designing evaluation frameworks for AI agents, including response quality, task completion, groundedness, hallucination detection, safety, latency, and cost. - Experience implementing LLMOps or MLOps practices, including prompt and model versioning, experimentation, monitoring, tracing, feedback collection, and continuous improvement. - Experience designing AI systems with strict requirements for security, responsible AI, compliance, auditability, data privacy, explainability, and tenant isolation. - Experience integrating conversational or agentic AI experiences with web applications, including Angular-based user interfaces. - Background in event-driven, workflow-based, service-oriented, batch, or hybrid processing architectures. - Experience modernizing legacy enterprise applications by introducing AI agents, intelligent automation, or reusable AI platform capabilities. - Experience leading large-scale technical transformations and successfully moving AI solutions from experimentation to secure, production-grade adoption.
Skills
AngularCompliance
