AI engineer for enterprise applications

Whitehall Resources currently require an experienced AI Engineer to work with a key client

• Own end-to-end delivery of LLM-enabled applications in agile sprints, spanning backend services, data orchestration, LLM pipelines, and front-end UI
• Act as the “CTO of the build,” making architecture and implementation decisions
• Ensure solutions convert into scaled production deployments
• Work side-by-side with strategic customer teams, often onsite (up to 30% travel)
• Diagnose root problems, understand context and customer pain points, and identify high-value AI opportunities
• Adapt, deploy, and iterate in live environments
• Build APIs (REST/GraphQL), orchestration pipelines, vector DB integrations, LLM frameworks (LangChain, Semantic Kernel), and UI components (React/Angular)
• Integrate with legacy systems and navigate ambiguity while shipping safely at speed
• Create libraries, SDKs, prompts, scaffolds, and documentation that can be reused across customer engagements
• Turn each successful project into a repeatable pattern
• Share field-tested insights with platform and product teams
• Shape internal tooling and contribute to the Now AI Platform roadmap and primitives
• Debug distributed systems, tune for latency, and implement monitoring and observability
• Deliver resilient, secure systems suitable for high-stakes enterprise contexts
• Use AWS, Azure, or GCP with CI/CD, containers, and infrastructure-as-code
• Lead implementation from zero to one, earning trust from architects, PMs, and customer teams
• Balance product sensibility (user value, MVP iteration) with long-term scalability

• Experience: In leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry
• Relevant Experience: 8+ years of software engineering, including 2+ years building systems in customer-facing or embedded roles
• System architecture: Proven ability to design and implement AI-native software in production environments
• Engineering depth: Strength in backend (Python, Node.js, Java), frontend (React, Angular), APIs (REST/GraphQL)
• LLM tooling: Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management
• Performance & observability: Skilled in debugging distributed systems, tuning for latency, and implementing monitoring
• Platform mindset: Can contribute to shared SDKs and tools, raising engineering velocity for the whole org
• Product sensibility: Prioritize for user value, MVP iteration, and long-term scale
• DevOps fluency: Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code
• 10+ years of software engineering experience (2+ in customer-facing or embedded roles)
• Backend (Python, Node.js, Java) and frontend (React, Angular) strength
• Hands-on LLM tooling: prompt chaining, vector search, context management
• Cloud and DevOps fluency

• Условий в вакансии нет