Senior AI Engineer

Overview

On Site
$140,000 - $150,000
Full Time

Skills

Artificial Intelligence
Amazon Web Services
Cloud Computing
Data Acquisition
Data Engineering
Data Extraction
Machine Learning (ML)
Large Language Models (LLMs)
Machine Learning Operations (ML Ops)
TensorFlow
PyTorch
Python
Hugging Face Transformer

Job Details

Must Have Skills :-

3+ years in a technical leadership role, building and deploying machine learning systems in production

Deep expertise in Python and modern AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers)

Experience with large language models (OpenAI, Anthropic, Cohere, open source LLMs) and prompt engineering

Not chat bot engineer, workflow, open source LLM s, info gathering, data extraction etc

Responsibilities:

Architect and implement advanced AI and machine learning systems that solve complex business problems

Lead the design and deployment of LLM-based applications using frameworks like LangChain, LlamaIndex, and vector databases

Develop end-to-end ML pipelines from data acquisition and model training to deployment and monitoring

Design and build AI copilots, agents, and generative workflows that integrate seamlessly into modern software ecosystems

Apply deep expertise in NLP, computer vision, or predictive modeling to build intelligent, real-time systems

Evaluate and fine-tune foundation models for custom enterprise use cases

Collaborate with cross-functional product, design, and engineering teams to define intelligent experiences

Explore and implement retrieval-augmented generation (RAG), semantic search, and multi-modal reasoning techniques

Contribute to internal AI frameworks, toolkits, and accelerators to speed up solution delivery

Mentor engineers on AI architecture, model lifecycle best practices, and ethical/secure use of machine learning

Requirements

8+ years of software engineering experience with a strong focus on AI/ML and intelligent systems

3+ years in a technical leadership role, building and deploying machine learning systems in production

Deep expertise in Python and modern AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers)

Experience with large language models (OpenAI, Anthropic, Cohere, open source LLMs) and prompt engineering

Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS) and scalable ML infrastructure

Knowledge of AI system design, data engineering for ML, model evaluation, and MLOps practices

Strong understanding of NLP, generative AI, embeddings, and semantic search

Experience integrating AI capabilities into full-stack applications and cloud-native environments, specifically within AWS.

Strong communication skills and a consulting mindset able to confidently lead client-facing discussions on AI strategy

Passion for experimentation, innovation, and shaping the future of applied AI

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