Senior Analytics Manager – AI Model, Prompt Engineering

Jobtailor; Illinois; On-site; USD 180,000 - 260,000; Full time

Job summary

Jobtailor is seeking a senior leader to steer AI engineering teams in delivering GenAI solutions across hybrid cloud and edge environments. You will align the team with company goals, drive scalable system design, and champion best practices across CI/CD, testing, and incident management.

The role requires deep expertise in AI architectures, data ecosystems, and cross-functional project management in matrixed organizations, with a track record of delivering enterprise-grade AI products.

Qualifications

• :Extensive software engineering leadership in AI and software teams.
• :Track record delivering GenAI solutions and enterprise-scale products across hybrid cloud and edge environments.
• Experience delivering complex cross-functional digital projects in matrixed organizations.
• Proven experience with project management including charters, scheduling and planning.
• Excellent interpersonal skills to address sensitive issues and influence others.
• Strong project management, team leadership, communication, analytical and organizational skills.
• Experience delivering software at scale; CI/CD, testing, deployments, incident management.
• Knowledge of APIs, microservices, cloud/edge architectures for AI components.
• Enterprise data ecosystems, data pipelines and data objects expertise.
• Cloud platforms (Azure, AWS, GCP) and AI workloads (Foundry/SageMaker/Bedrock).
• Snowflake and Cortex AI compute capabilities knowledge.
• GenAI system design: prompts, tool use, memory, RAG, LoRA concepts.
• GenAI model types: LLMs, SLMs, multimodal.
• LangChain/LangGraph familiarity.
• MCP and A2A protocols familiarity.
• AI evaluation, benchmarking, optimization across open-source and commercial models.
• GenAI metrics, A/B testing, human-in-the-loop validation.

Responsibilities

• Provide strong technical leadership and clear direction to align team with company goals and deliver advanced AI projects.
• Manage resources to ensure on-time delivery of high-quality results.
• Oversee team performance and foster learning by addressing training needs.
• Establish and supervise engineering best practices for consistency and excellence.
• Own the quality of engineering products, ensuring robust, reliable solutions.

Skills

AI project delivery

GenAI solutions

project management

CI/CD

unit testing

integration testing

scalable system design

APIs

microservices

data pipelines

Tools

Azure Foundry

SageMaker

Bedrock

EC2

S3

Snowflake

Cortex

LangChain

LangGraph

MCP

A2A protocols

Job description

• 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 the team as a whole, fostering a culture of learning by identifying and addressing training and development needs
• Establishing and supervising the implementation of engineering best practices to maintain consistency and excellence in development processes
• Taking ownership of the quality of engineering products, making sure all solutions are robust, reliable, and meet high standards

Requirements

• Extensive software engineering leadership experience with leading AI and software teams in agile, matrixed organizations
• Demonstrated track record of delivering GenAI solutions and enterprise-scale products across hybrid cloud and embedded/ edge environments
• Experience delivering complex cross-functional digital projects in matrixed organizations
• Proven experience with project management concepts including project charters, scheduling and planning projects and successful completion
• Excellent interpersonal skills are required to deal with sensitive issues, develop others, or influence others inside and outside the department to take specific actions
• Should have strong project management skills, team leadership skills, excellent communication skills, strong analytical and organizational skills
• Extensive experience with delivering software solutions at scale and complete grasp of fundamental concepts such as CI/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
• Expertise in 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 with Snowflake, including AI compute capabilities 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 as LoRA
• Deep knowledge of GenAI model types, including LLMs, SLMs, speech, multimodal, and real‑time models
• Experience with agentic orchestration frameworks such as LangChain, LangGraph
• Familiarity with MCP and A2A protocols
• Strong expertise in AI evaluation, model selection, benchmarking, and optimization across open‑source and commercial model ecosystems
• Strong foundation in AI products evaluation 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

Hard Skills

• AI project delivery
• GenAI solutions
• project management
• CI/CD
• unit testing
• integration testing
• scalable system design
• APIs
• microservices
• data pipelines

Soft Skills

• interpersonal skills
• team leadership
• communication skills
• analytical skills
• organizational skills