Apptad-Generative AI Engineer

Apptad Inc.
New York, NY, United States
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$110,000.0 - $130,000.0
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Automated Storage and Retrieval Systems Microsoft Azure Cloud Engineering Computer Programming Continuous Integration Python (Programming Language) Machine Learning Natural Language Processing Open Source Technology
+26 more
Tensorflow Search Technologies Systems Integration Management of Software Versions Enterprise Software Applications Feature Engineering Pytorch Large Language Models Multi-Agent Systems Prompt Engineering Model Validation Generative AI Build Management AI Platforms Kubernetes Information Technology Low Latency HuggingFace Machine Learning Operations Virtual Agents Api Design GPT Automation Anywhere Docker Programming Languages Microservices

Job description

We are seeking a highly skilled Generative AI Engineer with expertise in Large Language Models (LLMs), Python, Retrieval-Augmented Generation (RAG), and Agent Orchestration to design, build, and optimize next-generation AI solutions. In this role, you will work at the forefront of AI innovation, developing intelligent systems that enhance user experiences, automate business workflows, and deliver scalable AI-powered products. You will collaborate closely with cross-functional teams including data scientists, software engineers, product managers, and business stakeholders to bring generative AI applications from concept to production. The ideal candidate has hands-on experience with LLMs, prompt engineering, orchestration frameworks, model evaluation, and deploying AI solutions in cloud environments., * Design, develop, fine-tune, and optimize large language models (LLMs) for a wide range of business and product use cases.

  • Build and deploy generative AI applications using Python and AI/ML frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
  • Develop Retrieval-Augmented Generation (RAG) pipelines by integrating vector databases, embeddings, semantic search, and knowledge retrieval systems.
  • Implement and manage agent orchestration workflows using frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or similar multi-agent systems.
  • Conduct data preprocessing, feature engineering, and dataset preparation to support model training, fine-tuning, and evaluation.
  • Collaborate with engineering and product teams to integrate AI models and agent-based systems into production-grade applications and APIs.
  • Evaluate model and system performance using relevant metrics, and continuously improve accuracy, latency, scalability, and cost efficiency.
  • Design prompt strategies, guardrails, and monitoring approaches to ensure reliable and safe LLM outputs.
  • Stay current with the latest advancements in generative AI, LLM architecture, RAG, AI agents, and emerging research trends.
  • Ensure compliance with ethical AI principles, security standards, and data privacy regulations throughout the AI development lifecycle.

Requirements

  • Proven experience in developing, fine-tuning, and deploying large language models such as GPT, BERT, T5, LLaMA, or similar architectures.
  • Strong programming skills in Python with experience building AI/ML solutions in production environments.
  • Hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, and Hugging Face.
  • Solid understanding of natural language processing (NLP) concepts, prompt engineering, model evaluation, and fine-tuning techniques.
  • Experience designing and implementing RAG architectures, including embeddings, vector stores, document chunking, retrieval strategies, and grounding mechanisms.
  • Familiarity with agent orchestration frameworks and building multi-step or multi-agent AI workflows.
  • Experience with API development, microservices, and integrating AI capabilities into enterprise systems.
  • Working knowledge of cloud platforms such as AWS, GCP, or Azure for scalable AI deployment.
  • Strong analytical thinking, problem-solving ability, and effective collaboration skills.
  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field. Ph.D. is a plus.

Preferred Skills

  • Experience deploying and managing LLM applications with MLOps/LLMOps practices, including monitoring, versioning, and experimentation.
  • Familiarity with vector databases such as Pinecone, Weaviate, FAISS, Chroma, or Milvus.
  • Knowledge of Docker, Kubernetes, CI/CD pipelines, and scalable deployment patterns for AI services.
  • Experience with cloud-native AI services and model hosting infrastructure.
  • Understanding of AI safety, model governance, observability, and responsible AI practices.
  • Knowledge of additional programming languages is a plus.
  • Strong publication record, research background, or contributions to open-source AI projects

Benefits & conditions

  • $110,000-130,000 per year The of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a…

  • 24 days ago + *

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.careerjet.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

40 sec

Generative pre-trained transformer models powering code completions

lgonta lgonta +1 · WWC 2024

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · WWC 2025

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · WWC 2023

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

51 sec

Assessing GPT-4o performance for pull request feedback

Merrill Lutsky Merrill Lutsky · WWC 2025

3:22 min

Evaluating advanced artificial intelligence platforms for daily recruitment

Rudi Bauer Rudi Bauer +1 · Cappuccino with HR

Videos

See all

Related articles

See all