AI Solutions Engineer - Professional Services

About the role

The Professional Services AI Solutions Engineer plays a critical role in accelerating the effective adoption of AI tools and capabilities across Precisely’s Professional Services team.

Responsibilities

• Independently build AI agents to automate complex data mapping, schema conversion, and code migration tasks.
• Design "Configuration Agents" that auto-generate documentation and environment setups for product deployments.
• Audit Professional Services workflows to identify high-impact AI opportunities.
• Perform cost-benefit analyses, translating technical metrics into "hours saved" and "margin improvement" for leadership.
• Hands-on agentic engineering: design and code autonomous AI Agents using frameworks like Lang Graph, Crew AI, or Semantic Kernel.
• Build systems capable of multi-step reasoning, self-correction, and tool-calling.
• Team enablement & training: collaborate with Central AI Team's AI Enablement Lead on PS-specific training content.
• Self-driven governance & scaling: implement LLM Ops for PS-specific agentic solutions, operating within Precisely's AI Architecture Standards and in coordination with the Central AI Team's AI Platform Engineer for tooling, evaluation standards, and model governance.
• Agentic Solutions: leads the strategy, design, and delivery of agentic service offerings in Professional Services by leveraging MCP servers to connect AI agents with enterprise data and software solutions.
• Own customer adoption of MCP based solutions, driving scalable, governed, and LLM agnostic agent implementations that maximize existing automation investments.

Requirements

• Bachelor’s degree in computer science, Information Systems, Data Analytics, Business, or a related field.
• 3–5 years of experience supporting Professional Services delivery, consulting initiatives, or technology-enabled programs in a software or SaaS environment.
• Experience supporting technology adoption, change management, or enablement across cross-functional teams.
• Strong analytical and problem-solving skills with the ability to interpret data and derive actionable insights.
• Excellent written and verbal communication skills, with the ability to translate complex concepts for diverse audiences and non-technical stakeholders.
• Ability to simplify complex LLM concepts into actionable training for consultants, analysts, and partners.
• Experience working with stakeholders at multiple levels, including technical and non-technical partners.
• AI Enablement & Training background and excellent presentation skills a must.

Qualifications

• Strong proficiency in Python, with hands-on experience building or enhancing AI-enabled workflows or internal accelerators.
• PRACTICAL experience designing and implementing generative AI solutions, including Retrieval-Augmented Generation (RAG), vector databases, and API-based integrations.
• EXPERIENCE working with AI agent frameworks and orchestration tools such as LangGraph, CrewAI, Semantic Kernel, or LlamaIndex.
• SOLID working knowledge of AI/ML concepts and automation platforms sufficient to support enablement, training, and real-world solution delivery.
• Experience using enterprise LLM platforms (e.g., Anthropic Claude, OpenAI models), with sound judgment in evaluating outputs, limitations, and risk.

Skills

• Ability to identify and improve manual or repetitive Professional Services processes using AI or automation.
• CLEAR analytical and communication skills, with the ability to explain AI-driven outcomes to consultants and delivery stakeholders.
• COMFORT using generative AI tools (e.g., Microsoft Copilot, ChatGPT, Claude) and a growth mindset aligned to an AI-first organization.