AI Engineering Manager – AI & Data Development (Health)

Guidehouse•Austin, TX

1d•$118,000 - $196,000

About The Position

As an AI Engineering Manager at Guidehouse, you will lead the design, development, deployment, and optimization of AI solutions, including foundational model fine-tuning and agentic workflow orchestration primarily within the healthcare sector and expanding into additional business verticals. You will play a critical role in shaping Guidehouse’s AI engineering strategy, ensuring solutions are production-grade, secure, compliant, and capable of delivering meaningful client and operational impact. Your expertise will help revolutionize healthcare delivery, enhance user experience, reduce operational costs, and maintain adherence to industry regulations such as HIPAA. This role is a hands-on delivery leader and trusted client partner, responsible for independently owning projects/workstreams, driving agile execution, and translating healthcare business needs into scalable AI technology and data solutions. The role emphasizes delivery excellence, client impact, and collaboration.

Requirements

US Citizenship or a Green Card is required
Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or a related field.
A minimum of FIVE (5) years of engineering experience with cloud-native systems (APIs, microservices, containerization, serverless architectures).
A minimum of ONE (1) year of deep, hands-on experience designing and deploying agentic AI systems (RAG, orchestration, tool use, workflow automation) in production.
A minimum of THREE (3) years working with leading AI platforms (OpenAI, Claude, Vertex AI) and open-source LLM frameworks, including building abstraction layers for multi-provider pipelines.
A minimum of FIVE (5) years of programming experience in Python, Java, or equivalent languages, with familiarity in logging, monitoring, and agent/LLM observability.
A minimum of FIVE (5) years deploying production systems using CI/CD, infrastructure-as-code (Terraform, Helm), and modern monitoring/debugging tools.
Delivered 3 to 5 medium or large-scale AI/LLM projects of significant business value.
ML/LLM Engineering Skills Strong command of Python and modern AI/ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers).
Experience deploying and optimizing models using serving/inference frameworks (Triton, TensorRT, VLLM, TGI, etc.).
Familiarity with MLOps practices for CI/CD, continuous training, observability, and automated monitoring.
Domain & Compliance Knowledge Understanding of healthcare interoperability standards (FHIR, HL7, EDI) and regulatory frameworks (HIPAA, SOC2) is preferred.
Collaboration & Leadership Proven ability to work with business, engineering, and IT teams to incorporate AI/ML capabilities into enterprise solutions.
Strong analytical problem-solving skills and the ability to operate in ambiguous, fast-moving environments.
Excellent communication skills, enabling effective collaboration across internal and client teams.

Nice To Haves

Additional certifications in AI, cloud platforms, data platform (Databricks, Snowflake) or agentic tools are a strong plus.
Prior experience as an Agentic AI Engineer in an enterprise setting.
Familiarity with compound AI system architectures, orchestration frameworks, agent registries, and event/stream-based systems.
Strong understanding of the AI-native paradigm, blending cloud-native engineering with LLM-driven architectures for performance, modularity, and efficiency.
Experience delivering agentic solutions across multiple industries, such as healthcare and finance.

Responsibilities

AI & Agentic Systems Engineering Design, architect, and deploy enterprise-ready AI agents, including retrieval components, orchestration layers, policy-based routing, evaluation harnesses, and lifecycle observability.
Develop and manage multi-provider abstraction layers across AI platforms (OpenAI, Anthropic, Google/Vertex AI, etc.) to support scalable and portable AI solutions.
Build cloud-native AI systems, using Kubernetes, Docker, microservices, serverless computing, event-driven architectures, CI/CD, and comprehensive observability stacks.
Platform & Workflow Integration Tailor and implement industry-specific agentic workflows (healthcare, finance, energy) to automate complex processes and drive measurable outcomes.
Partner with cross-functional stakeholders to define use cases, rapidly prototype solutions, and deploy robust agentic workflows into production and client environments.
Conduct design workshops, POCs, and joint engineering sessions to support client enablement and adoption of AI-driven solutions.
Performance, Compliance & Governance Define and monitor key metrics for agent accuracy, safety, latency, cost-efficiency, and reliability.
Ensure AI solutions comply with applicable industry and regulatory standards (HIPAA, SOC 2, etc.).
Create and maintain detailed documentation across model development, t raining, fine-tuning, deployment, and operational processes.
Leadership & Knowledge Sharing Provide technical leadership, mentorship, and guidance to junior engineers and contributing team members.
Develop reusable patterns, best practices, and internal frameworks that influence Guidehouse’s AI engineering strategy and client roadmaps.

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Position may be eligible for a discretionary variable incentive bonus
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life
Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend