Senior AI Engineer - Enterprise Applications

Overview:

Senior AI Engineer - Enterprise Applications

About the Role

We are seeking a highly skilled Senior AI Engineer to help design, build, and operationalize intelligent systems that address complex, high-impact challenges within a professional services environment. This role sits within an innovation-focused engineering group responsible for delivering secure, scalable, and production-grade AI solutions that support both client-facing and internal business workflows.

You will work closely with business leaders, domain experts, data scientists, and infrastructure teams to translate nuanced problem statements into measurable, real-world AI capabilities. From early discovery and prototyping through enterprise deployment and monitoring, you will contribute across the full lifecycle of applied AI solutions, with an emphasis on reliability, governance, and long-term maintainability.

This is an opportunity to operate at the intersection of modern AI engineering, cloud-native architecture, and mission-critical business systems , helping shape how advanced AI is responsibly deployed at enterprise scale.

What You'll Do

Design & Build Applied AI Solutions

• Partner with stakeholders to identify high-value AI use cases, define clear success metrics (e.g., efficiency gains, quality improvement, risk reduction), and architect solutions aligned to business outcomes.
• Develop AI-powered applications using Python and modern frameworks such as OpenAI / Azure OpenAI, Hugging Face, LangChain, and LangFlow.

Retrieval-Augmented Generation & Intelligent Workflows

• Design and maintain RAG pipelines leveraging vector databases and structured knowledge sources.
• Build AI-driven agents capable of orchestrating multi-step workflows and automating complex tasks.

Scalable Engineering & Reusability

• Produce reusable components, shared libraries, and documented patterns that support consistent AI development across teams.
• Promote engineering best practices that ensure solutions are extensible, testable, and sustainable.

Model Evaluation, Quality, & Governance

• Implement evaluation frameworks to measure LLM accuracy, robustness, safety, and alignment with intended use cases.
• Ensure AI systems comply with organizational standards for security, privacy, and responsible AI usage.

Production Readiness & Platform Enablement

• Support CI/CD workflows, containerization (Docker), and orchestration (Kubernetes) to enable reliable production deployments.
• Collaborate with infrastructure and security partners to support hybrid cloud and on-prem environments handling sensitive data.

Stakeholder Enablement & Advisory

• Serve as a trusted technical advisor to non-technical partners on prompt design, model selection, and architecture tradeoffs.
• Support pilot programs, user onboarding, feedback cycles, and adoption measurement.

Technology Exploration & Thought Leadership

• Evaluate emerging tools, open-source technologies, and vendor platforms to inform AI platform strategy.
• Contribute to internal knowledge sharing, documentation, and best-practice guidance.

What You Bring

Experience & Background

• Bachelor's degree in Computer Science or a related discipline (or equivalent practical experience).
• 7+ years of experience building and delivering software solutions in professional services, enterprise, or regulated environments.
• Demonstrated hands-on experience deploying AI-enabled systems into production.

Core AI & Engineering Skills

• Strong Python development skills and experience implementing RAG architectures and AI agent frameworks.
• Familiarity with vector databases (e.g., Pinecone or similar) and integrating structured and unstructured data sources.
• Experience building multi-service AI solutions, particularly within Azure-based ecosystems.

Cloud, DevOps, & Deployment

• Working knowledge of cloud services such as Azure AI services, Cognitive Search, Cosmos DB, or equivalent platforms.
• Experience with Docker, Kubernetes, and CI/CD pipelines supporting secure, scalable deployments.

Evaluation, Security, & Compliance

• Experience designing or using LLM evaluation frameworks (e.g., Promptfoo, OpenAI Evals, LangSmith).
• Comfort operating in environments with strict security, privacy, and governance requirements.

Communication & Business Acumen

• Ability to perform stakeholder discovery, clarify ambiguous problems, and articulate ROI.
• Strong communication skills, with the ability to explain complex technical concepts to diverse audiences.

Domain Exposure (Preferred, Not Required)

• Experience supporting knowledge-intensive domains such as legal, compliance, research, or document-heavy workflows.

Why This Role

This role offers the chance to build real, production-grade AI systems -not just prototypes-while collaborating with highly skilled professionals across engineering, business, and domain specialties. If you enjoy turning complex problems into elegant, reliable AI solutions and want to influence how intelligent systems are responsibly deployed at scale, this opportunity offers both depth and impact.