Senior Analytics Manager AI Model & Prompt Engineering

Job Summary:
Join theAI Engineeringteam of Cat Digital and take charge of leading and coordinating a team dedicated to building advanced generative AI solutionsincluding intelligent agents digital assistants and other innovative capabilities. You will shape the development ofcutting-edgeproducts that redefine how customersand dealersinteract with technology through AI-driven experiences.

What You Will Do:

• Providing strong technical support and clear direction to ensure the team is aligned with company goals and capable of delivering advanced AI projects.

• Managing resources efficiently to ensure projects are completed on schedule and to a high standard.

• Overseeing the performance of both individual team members and theteam as a whole fosteringa culture of learning byidentifyingand addressing training and development needs.

• Establishing and supervising the implementation of engineering best practices tomaintainconsistency and excellence in development processes.

• Taking ownership of the quality of engineering products making sure all solutions are robust reliable and meethigh standards.

What You Will Have:

• Software Development:Expertknowledge of software development tools and activities; ability to produce software products or systems in line with product requirements.

• Software Integration Engineering:Extensiveknowledge of software integration processes and functions; ability to design develop andmaintaininterfaces and linkage to alternative platforms and software packages.

• Software Quality Assurance and Testing:Extensiveknowledge of software quality assurance and testing; ability to applyappropriate processes tools and techniques for assuringa high levelof quality in computer software products and systems.

• Organizational Leadership:Extensiveknowledge of leadership concepts and ability to use strategies and skills to enlist others in settingembracingand achievingobjectives.

Considerations For Top Candidates:

• Extensive software engineering leadership experience withleading AI and software teams in agile matrixed organizations

• Demonstratedtrack recordof delivering GenAI solutions and enterprise-scale products across hybrid cloud and embedded/edgeenvironments.

• Experience delivering complex cross-functional digital projects in matrixed organizations.

• Proven experience with project management concepts including project charters scheduling and planningprojectsand successful completion.

• Excellent interpersonal skills areto deal with sensitive issues develop others or influence others inside and outside the department to take specific actions.

• Shouldhave strong project management skills team leadership skills excellent communication skills strong analytical and organizational skills.

• Extensive experiencewith deliveringsoftwaresolutions atscale and complete graspof fundamentalconcepts such asCI/CD unit testing integration testing feature flags blue/green deployments canary deployments; experience with incident management

• Solid software engineering and distributed systems knowledge; understanding of scalable system design APIs microservices and cloud/edge architectures enabling effective integration of AI components into production-grade applications.

• Expertisein enterprise platforms and data ecosystems hands-on experience with delivering data pipelines and data objects

• Working knowledge of major cloud platforms such as Azure AWS or GCP including designing and managing scalable secure AI workloads using services such as Azure Foundry SageMaker Bedrock EC2 and S3

• Experience withSnowflake including AIcomputecapabilities such as Cortex.

• Deep knowledge of GenAI system design including prompt engineering patterns such as system prompts few-shot chain-of-thought and structured output; agentic system concepts including tool use planning multi-agent orchestration memory guardrails; vector databases concepts such as chunking embeddings; patterns such as RAG (sparse dense hybrid); fine-tuning approaches such asLoRA.

• Deep knowledge of GenAI model types including LLMs SLMs speech multimodal andreal-timemodels

• Experience with agentic orchestrationframeworkssuch asLangChainLangGraph

• Familiarity withMCPand A2Aprotocols

• Strongexpertisein AI evaluation model selection benchmarking and optimization across open-source and commercial model ecosystems.

• Strong foundationin AIproductsevaluation and performance measurement with deep familiarity with evaluation methodologies including GenAI-specific metrics (e.g. RAG quality output reliability) A/B testing and human-in-the-loop validation to ensure robustness and consistency in production systems.