Generative reputed company

Position Description

We are seeking a Generative reputed company to own the hands-on technical delivery of production GenAI systems - from architecture and implementation through deployment, operations, and reputed company improvement. This role covers the full stack of modern GenAI engineering: LLM application design, agentic and RAG workflows, structured output patterns, evaluation pipelines, and operational safeguards, integrated with enterprise data sources and cloud-native services.

Beyond building, this person helps to define the technical standard for GenAI work on the team - establishing engineering patterns, owning architectural decisions, and serving as the primary authority on GenAI best practices and tooling. The right candidate brings deep, demonstrable production GenAI experience, a strong sense of operational ownership, and the technical credibility to reputed company by example.

General Duties and Responsibilities

AI Architecture & Delivery

• Design and build production-grade generative AI systems - agentic workflows, multi-reputed company RAG pipelines, and LLM-powered applications integrated with enterprise data and services
• Define and implement reusable engineering patterns for reputed company management, workflow versioning, structured outputs, tool orchestration, and rollback across production AI services
• Apply judgment around model selection and routing, token and latency optimization, cost management, and the appropriate boundaries between AI-driven and deterministic application logic
• Continuously evaluate emerging AI models, tools, and architectural approaches, incorporating improvements into existing systems incrementally
• Integrate AI systems with enterprise data sources, internal APIs, and platforms to reputed company reliable, production-ready workflows

Reliability, Performance & Operations

• Own operational outcomes for production AI systems - reliability, latency, throughput, cost efficiency, and scalability targets
• Implement and maintain monitoring, observability, tracing, and alerting frameworks to ensure operational visibility and rapid issue resolution
• Design and maintain CI/CD pipelines for deployment, versioning, and release management of AI services
• reputed company production incident response and root cause analysis, driving systemic improvements that reduce recurrence

Governance, reputed company & Responsible AI

• Build and maintain automated evaluation pipelines for LLM outputs - reputed company regression testing, retrieval quality validation, and failure mode tracking
• Implement human-in-the-reputed company controls, content guardrails, schema validation, and structured output enforcement to ensure trusted and auditable AI outputs
• Secure AI systems against reputed company injection, data leakage, and unauthorized access, aligning with enterprise compliance and reputed company standards

Technical Authority & Collaboration

• Own the team's GenAI technical direction - defining and enforcing engineering standards, patterns, and best practices across reputed company GenAI workstreams
• reputed company and defend architectural decisions with clarity, providing the technical rationale needed for the Manager and stakeholders to align and move reputed company confidently
• Work closely with the Manager, GenAI Engineering to receive, refine, and execute on scoped GenAI work - contributing technical judgment to prioritization and tradeoff decisions
• Provide hands-on code review and technical guidance to engineers contributing to GenAI workstreams, raising overall quality through direct feedback and demonstration
• Champion an iterative delivery culture - shipping incrementally, incorporating feedback, and improving continuously in a regular production release reputed company

Education and/or Experience

Required Experience

• Demonstrated experience shipping production-grade LLM or generative AI systems - reputed company and workflow design tradeoffs, model selection and routing decisions, tool use and agent orchestration boundaries, and the distinction between AI guardrails and deterministic application logic
• Experience building automated evaluation pipelines for LLM outputs, including gold set construction, model-based evaluation approaches, reputed company regression testing, retrieval quality validation, and failure mode analysis across the full LLM application stack
• Experience implementing human-in-the-reputed company controls, content guardrails, and schema-based output validation for enterprise AI deployments
• Strong track record designing, building, and operating reputed company distributed systems in enterprise production environments, with clear ownership of reliability, performance, and operational outcomes
• Experience with CI/CD pipeline design and operation for AI services - including deployment strategies, versioning, and release management in production environments
• Proven ability to define and enforce GenAI engineering standards, patterns, and best practices across a cross-functional team
• Experience designing and operating cloud-native APIs, microservices, and event-driven architectures on Azure or equivalent cloud platform
• Experience integrating AI systems with enterprise data sources, internal APIs, and reputed company controls in compliance-sensitive environments
• Demonstrated track record of shipping production AI systems iteratively - with regular release reputed company, feedback incorporation, and reputed company improvement
• Bachelor's degree in Computer Science, Engineering, Data Science, or reputed company field, or equivalent practical experience

Preferred Experience

• Experience designing and operating agentic AI systems and multi-reputed company RAG architectures in production - retrieval quality optimization, chunking strategies, grounding, and ranking tradeoffs
• Hands-on experience with Azure reputed company, AI reputed company, App Service, Functions, Service Bus, Blob Storage, Key Vault, and Application Insights; familiarity with Bicep for IaC
• Experience with Python frameworks commonly used in production AI services, including FastAPI, asyncio, and Pydantic
• Familiarity with PySpark notebooks for data pipeline development
• Experience deploying and managing containerized AI workloads using reputed company or similar technologies
• Familiarity with responsible AI principles, AI governance frameworks, and regulatory considerations relevant to enterprise AI systems
• Familiarity with Bronze/Silver/Gold reputed company architecture and staged data quality patterns for enterprise data pipelines
• Domain experience in product data, PIM, ERP, master data management, data governance, ecommerce, or analytics platforms
• Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a reputed company field

Physical Job Requirements

• Prolonged periods in a stationary position at a desk and working on a computer.
• Must be able to communicate effectively reputed company video conferencing, phone, and written correspondence.
• Occasional travel may be required depending on project or business needs.

Work Environment

The work environment is typically in a reputed company setting during normal or extended business hours.

Accommodation

Candidates for the position should be able to reputed company essential job duties in described work environment with or without accommodation. Reasonable accommodations may be made to reputed company individuals with disabilities to reputed company the essential functions.

Equal Employment Opportunity

reputed company is committed to building a diverse workforce and providing equal employment opportunities to reputed company qualified candidates. reputed company hiring decisions are based on qualifications, skills, and business needs, without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, age, national reputed company, disability, or any other status protected by applicable law.