AI-ML Engineer

Harris ComputerBolivia, NC
3d

About The Position

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 mission of Harris Global Business Services (GBS) is to exclusively serve Harris BUs across all verticals as a turn-key Center of Excellence for global offshoring in different countries around the world. GBS offers services to support Harris BUs in recruiting, hiring, onboarding, training and retaining highly qualified employees based on BU requirements. We are currently building new or expanding existing offshore teams in Costa Rica, India and Bolivia. GBS creates a customized recruitment campaign to hire Harris FTEs across the full spectrum of services, including R&D, Customer Support, Professional Services and Sales roles, along with corporate services including Finance, CIT, M&A, HR, Payroll, Compliance and Legal. We are committed to supporting our diverse, highly skilled, multi-national workforce with an outstanding corporate culture and strong engagement initiatives for all employees. GBS was created based on the staff augmentation model developed by Harris Computer in Costa Rica. Incorporated in October 2020, Harris Adelante Servicios SRL currently supports more than 12 business units with 50 employees working across all vertical markets, including Harris Healthcare, Public Sector, Utilities and Quebec groups.

Requirements

  • 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)
  • 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

Nice To Haves

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

Responsibilities

  • 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
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