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We are searching for a Senior nAI Engineer to become part of our team. This role puts you in charge of the entire development, deployment, and operational journey of enterprise-grade AI-powered applications. It draws together backend engineering, LLM integration, cloud infrastructure, and AI platform operations to bring scalable GenAI solutions into live production settings. You will team up with AI/DS, Product, and DevOps groups to construct and expand AI-driven applications, safeguarding reliability, observability, performance optimization, and operational excellence throughout the entire AI SDLC. This position further includes backing GenAI-assisted development approaches, aiding in the growth of the client's enterprise AI SDLC processes, participating in AI Beauty Chat initiatives via agentic micro-pod delivery models, and handling System Steward obligations across AI platform efforts.
- Craft, build, launch, and support backend services that drive AI/LLM-powered applications
- Assume complete responsibility for GenAI feature delivery, starting from initial development all the way to production support
- Link and administer LLM APIs, such as OpenAI, inside enterprise production settings
- Build out APIs, orchestration layers, and microservices to power agentic AI workflows
- Adjust LLM systems to improve latency, resiliency, retry handling, fallback logic, and cost management
- Configure CI/CD pipelines along with observability, monitoring, and logging capabilities for AI services
- Team up with AI/DS, Product, DevOps, and platform groups to ease delivery and reinforce reliability
- Function within Azure cloud settings and distributed systems, spanning Redis, Kafka, and SQL/NoSQL databases
- Support MCP integrations, agentic memory efforts, and AI orchestration frameworks
- Promote GenAI-assisted development approaches and contribute to scaling the client's AI SDLC processes
- Play a role in AI Beauty Chat delivery through agentic micro-pod execution models
- Handle System Steward obligations within agentic micro-pods
- At least 3 years of experience relevant to this role
- Primary specialization in AI Engineering with an emphasis on backend systems
- Strong background in Python for backend engineering
- Proven experience delivering and running production-grade GenAI/LLM applications from end to end
- Direct, hands-on work with OpenAI or comparable LLM APIs within production contexts
- Proficiency in prompt engineering along with various orchestration techniques
- Experience tackling operational issues tied to LLMs, covering latency, retries, fallback strategies, observability, and cost efficiency
- Firm grasp of distributed system design and scalable backend architecture
- Background in CI/CD practices, DevOps processes, and Azure cloud platforms
- Experience weaving GenAI into the SDLC, including AI-assisted coding, testing, deployment, and release workflows
- Practical familiarity with SQL/NoSQL databases, Redis, and Kafka
- Strong ability to communicate clearly and effectively
- Excellent English proficiency (B2 level or higher)
- Background working with agentic workflow patterns
- Practical exposure to Databricks and MCP