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AI/ML Engineer

Roles & Responsibilities

  • 4+ years of experience with large language models (LLMs) and NLP using LangChain, LangGraph, and LlamaIndex
  • 3+ years of experience developing APIs/microservices with Java, .NET, or JavaScript
  • 3+ years of experience working with generative AI tools (e.g., OpenAI’s GPT, Anthropic Claude, Google Gemini)
  • 3+ years of Python development and experience with ML frameworks (TensorFlow, PyTorch) and SQL databases

Requirements:

  • Build, deploy, and operate AI/ML systems in production, focusing on robustness and scalability
  • Productionize models using APIs, microservices, or batch pipelines, and implement LLM-based systems (RAG, embeddings, evaluation, prompt optimization)
  • Maintain model monitoring, logging, and retraining workflows; ensure data quality and availability with data engineers; follow MLOps, DevOps, and cloud standards
  • Troubleshoot model, data, and infrastructure issues

Job description

Here at Harris, you’ll be working as part of 5 different business verticals, Public Sector, Healthcare, Utilities, Insurance and Private sector, with over 12,000 employees and more than 100,000 customers located in 200 countries around the globe. We need your help to keep growing and we hope you can become an integral part of the Harris family.

We are looking for an AI/ML engineer to help us build, deploy, and operate AI and machine-learning systems in production. You’ll focus on engineering robustness and scalability, bridging data science and software engineering to ensure models perform reliably in real-world applications.

Primary Functions:

  • Build and deploy ML and Generative AI solutions into production systems
  • Productionize models using APIs, microservices, or batch pipelines
  • Implement LLM-based systems (RAG, embeddings, evaluation, prompt optimization)
  • Optimize performance, latency, cost, and reliability of AI services
  • Maintain model monitoring, logging, and retraining workflows
  • Work with data engineers to ensure data quality and availability
  • Follow established MLOps, DevOps, and cloud standards
  • Troubleshoot model, data, and infrastructure issues

Job Qualifications:

The qualifications we are looking for are mixture of work experience and educational background.

They are split into Minimum Qualifications (must have) and Additional Qualifications (nice to have) along with soft skills (competencies) needed for the role:

Minimum Qualifications:

  • 4+ years of experience with large language models (LLMs) and natural language processing (NLP) using: LangChain, LangGraph, LlamaIndex
  • 3+ years of experience supporting and developing API/Microservices with Java, .Net or JavaScript.
  • 3+ years of experience working with generative AI tools (e.g., OpenAI’s GPT, Anthropic Claude, Google Gemini).
  • 3+ years of experience working as developer with Python.
  • 3+ years of experience with machine learning frameworks (e.g., TensorFlow, PyTorch)
  • 3+ years of experience working with relational databases (SQL)

Additional Qualifications:

  • AI certifications
  • ML certifications
  • Cloud certifications (AWS, Azure)

Soft Skills:

  • Demonstrated track record of working effectively within a collaborative and cohesive, team-based environment
  • Outstanding customer service and organizational skills
  • Exceptional analytical, troubleshooting, and problem-solving skills

The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. It is not designed to be utilized as a comprehensive list of all duties, responsibilities, and qualifications required of employees assigned to this job.

Working Environment:


This job operates in a professional office environment or remote home office location. This role routinely uses standard office equipment such as computers, phones, photocopiers, filing cabinets and fax machines.  Periods of stress may occur. 

This role may occasionally encounter Protected Health Information, Personal Identifiable Information or Privacy Records, and it is essential that all employees adhere to confidentiality requirements as outlined in the Employee Handbook and Harris’ Security and Privacy policies, as well as apply the concepts learned in the annual Security Awareness training.

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