AL/ML Technical Lead

Booz Allen Hamilton

Atlanta (GA)

On-site

USD 128,700 - 292,000

Full time

14 days+
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Job summary

Booz Allen Hamilton is seeking an AI / ML Technical Lead in Atlanta, GA, to drive the technical direction of mission-critical AI systems supporting Public Health. This role involves leading the design and implementation of scalable machine learning solutions while collaborating with engineers.

The ideal candidate will have extensive experience in AI technologies, Python programming, and a strong understanding of data governance in public health applications.

Qualifications

  • 5+ years of experience designing, developing, and deploying machine learning and AI solutions using Python.
  • Experience with Generative AI, LLMs, AI agents, or RAG systems in enterprise environments.
  • Experience with data engineering using PySpark, SQL, and Palantir Foundry.

Responsibilities

  • Lead the design and development of scalable AI / ML systems using PySpark and Palantir Foundry.
  • Architect generative AI solutions including AI agents and RAG pipelines.
  • Design and implement agent architectures with memory and orchestration.

Skills

Designing machine learning solutions
Developing AI systems
Python programming
Generative AI technologies
Data engineering with PySpark
ML frameworks like TensorFlow
MLOps platforms integration

Education

Bachelor's degree in Computer Science or related field

Tools

PySpark
Palantir Foundry
MLflow
Azure
Databricks

Job description

Position Overview

As an AI / ML Technical Lead, you will define and drive the technical direction of mission‑critical AI systems supporting Public Health and Safety. You will lead the design and implementation of scalable machine learning and generative AI solutions, including AI agents, retrieval‑augmented generation (RAG) systems, and evaluation frameworks that ensure reliability, safety, and mission alignment.

You will serve as a technical authority across a community of engineers, partnering with data engineers, architects, product owners, and stakeholders to shape enterprise AI strategy, architecture standards, and delivery practices. Your work will span end‑to‑end AI system design—from data pipelines and modeling to agent orchestration, memory or state management, retrieval optimization, and production deployment.

In this role, you will also lead the development of AI evaluation strategies, prompt engineering workflows, and governance frameworks using tools such as MCP, Prompt Buddy, Codex, Claude, and OpenEvidence. You will ensure systems are performant, explainable, secure, and compliant with public health data privacy and ethical standards. This position is located in Atlanta, GA.

Responsibilities
  • Lead the design and development of scalable AI / ML systems using PySpark and Palantir Foundry for public health mission applications.
  • Architect generative AI solutions, including AI agents, MCP‑enabled workflows, Prompt Buddy integrations, and RAG pipelines.
  • Define AI evaluation frameworks covering performance benchmarking, retrieval optimization, safety validation, and production monitoring.
  • Design and implement agent architectures with memory, state management, orchestration, and structured or unstructured data interaction.
  • Integrate advanced AI tools such as Codex, Claude, and OpenEvidence into enterprise AI workflows and platforms.
  • Establish data governance, privacy, anonymization, documentation, and ethical AI standards across AI / ML systems.
Qualifications
  • 5+ years of experience designing, developing, and deploying machine learning and AI solutions using Python.
  • 5+ years of experience with Generative AI, LLMs, AI agents, or RAG systems in enterprise environments.
  • 3+ years of experience with AI agents, MCP frameworks, or AI evaluation strategy development.
  • Experience with ML frameworks such as TensorFlow or PyTorch for production model development.
  • Experience with data engineering using PySpark, SQL, and Palantir Foundry, including Foundry AIP.
  • Experience with MLOps platforms such as MLflow and cloud environments such as Azure or Databricks.
  • Experience integrating or working with AI tooling such as Codex, Claude, Prompt Buddy, or OpenEvidence in enterprise settings.
  • Knowledge of public health, healthcare, or government data systems and associated governance practices.
  • Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
  • Bachelor's degree in Computer Science, Engineering, or Data Science.
Nice if you have
  • Experience working in healthcare, biomedical, or government public health AI / ML environments.
  • Experience with open‑source LLMs such as LLaMA, Gemma, or Phi.
  • Experience with conversational AI, chatbot systems, or full‑stack AI application development.
  • Experience with containerization, CI/CD, orchestration, and production MLOps pipelines.
  • Experience with Agile delivery environments and tools such as JIRA.
  • Experience writing technical documentation and presenting AI / ML architecture decisions to a broad range of audiences.
  • Knowledge of enterprise AI governance, compliance, and ethical AI frameworks.
  • Knowledge of AI systems for retrieval, ranking, and decision‑support in high‑stakes environments.
  • Ability to collaborate effectively in matrixed, cross‑functional organization and design and deploy scalable AI systems involving retrieval optimization, memory or state management, and agent orchestration.
  • Master's degree in Computer Science, Data Science, AI / ML, or a related field.
Vetting

Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client.

Compensation

Salary is $128,700.00 to $292,000.00 (annualized USD). The posting will close within 90 days from the posting date.

EEO Statement

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

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