Sr Enterprise Solutions Applied AI Engineer

This is a hybrid role blending hands-on delivery with technical ownership, evaluation rigor, and cross-functional leadership. 1. End-to-End Ownership of Complex AI Services (55% of time) Own the development of a complex AI service or GenAI feature, delivering from concept through production rollout and ongoing iteration. Translate ambiguous business requirements into concrete user stories, acceptance criteria, and technical implementation plans. Integrate agentic solutions with enterprise systems (e.g., CRMs, ERPs, HR platforms, data warehouses, internal APIs) and ensure production-grade performance through rapid iteration and troubleshooting. Lead pilot launches and transitions, including documentation, user enablement, and stakeholder alignment. 2. Multi-Step Agent Architecture, Evaluation & Operations (30% of time) Lead the design and implementation of multi-step agents, including tool/function calling, retrieval, state management, and human-in-the-loop oversight where required. Develop evaluation approaches (test suites, golden datasets, regression checks) and optimize solutions for accuracy, latency, reliability, and cost. Implement production observability (logging, tracing, monitoring) and contribute to runbooks and incident response processes for AI services. 3. Reusable Patterns, Standards & Mentorship (15% of time) Extract successful patterns from delivery work to create reusable libraries, templates, and reference implementations for other teams. Lead technical reviews and share best practices for secure, reliable, and user-trustworthy agentic systems. Mentor and coach P1-P2 engineers through code reviews, design reviews, and day-to-day execution. 8+ years of experience in software engineering, including ownership of production services. 3+ years building and deploying AI/ML or Generative AI solutions that deliver measurable business results in production. Strong proficiency with LLM application patterns: prompt engineering, Retrieval-Augmented Generation (RAG), and tool/function calling within agentic systems. Experience with agent frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, Microsoft Agent Framework, or similar). Hands-on experience with enterprise integrations, authentication/authorization, and secure API design. Operational excellence: familiarity with logging, tracing, monitoring, performance tuning, and cost management for AI applications. Strong communication skills and demonstrated ability to lead cross-functional delivery with business and technical stakeholders. Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Ideal Candidate Profile: Who Thrives in This Role Accountable Owner: You take end-to-end ownership and ensure solutions are deliverable, operable, and adopted. Field-Focused Problem Solver: You get energized by embedding with users, mapping real workflows, and making tangible improvements. Pragmatic Architect: You design solutions that are robust and maintainable, and you know when to keep things simple. Evaluation Mindset: You build measurement into the product and invest in test coverage and monitoring to keep quality stable over time. Translator: You communicate tradeoffs clearly to both executives and engineers and bridge business needs with technical implementation. Mentor: You raise the bar for the team through coaching, reviews, and reusable patterns.