Senior AI Engineer

Next Ventures; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Next Ventures is seeking an AI Engineer to design, develop, and deploy AI-powered applications that solve real-world business problems. You will collaborate with software engineers, data scientists, product managers, and business stakeholders to build, integrate, and optimize AI models and systems.

The ideal candidate has a strong software engineering foundation, experience with ML/AI technologies, and the ability to take AI solutions from concept through production.

Qualifications

• Experience developing and deploying AI/ML solutions.
• Strong Python programming and software engineering practices.
• Experience with cloud platforms (AWS/Azure/GCP).

Responsibilities

• Design, develop, and deploy AI-powered applications, models, and services.
• Build AI solutions using ML, LLMs, and generative AI technologies.
• Develop AI pipelines for data processing, model training, evaluation, and deployment.
• Integrate AI into existing apps and workflows.
• Work with structured and unstructured data for model development.
• Evaluate model performance and optimize for production.
• Collaborate with cross-functional teams and ensure responsible AI practices.

Skills

Python

ML frameworks

APIs / production deployments

Cloud platforms

Analytical skills

Communication

Team collaboration

Tools

Docker

Kubernetes

CI/CD

MLOps

LLM frameworks

Embeddings/vector search

Job description

AI Engineer

Job Overview

We are seeking an AI Engineer to design, develop, and deploy AI-powered applications and solutions that solve real-world business problems. This individual will work closely with software engineers, data scientists, product managers, and business stakeholders to build, integrate, and optimize AI models and intelligent systems.

The ideal candidate has a strong software engineering foundation, experience working with machine learning and modern AI technologies, and the ability to take AI solutions from concept through production.

Key Responsibilities

• Design, develop, and deploy AI-powered applications, models, and services.

• Build and integrate solutions using machine learning, large language models (LLMs), and generative AI technologies.

• Develop AI pipelines for data processing, model training, evaluation, and deployment.

• Integrate AI capabilities into existing applications, APIs, and business workflows.

• Work with structured and unstructured data to support AI model development and performance.

• Implement techniques such as prompt engineering, retrieval-augmented generation (RAG), and vector search where appropriate.

• Evaluate model performance, accuracy, scalability, reliability, and cost.

• Optimize AI systems for production environments, including monitoring, troubleshooting, and continuous improvement.

• Collaborate with cross-functional teams to translate business requirements into practical AI solutions.

• Follow best practices for responsible AI, data privacy, security, and model governance.

• Stay current with emerging AI frameworks, tools, and industry developments.

Required Qualifications

• Experience developing and deploying AI or machine learning solutions.

• Strong programming skills in Python and familiarity with common software engineering practices.

• Experience with AI/ML frameworks, libraries, and model development tools.

• Familiarity with large language models, generative AI, and related technologies.

• Experience building APIs, integrating services, and deploying applications into production.

• Understanding of data processing, model evaluation, and performance optimization.

• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.

• Strong analytical, problem-solving, and communication skills.

• Ability to work collaboratively across engineering, data, and product teams.

Preferred Qualifications

• Experience with LLM frameworks, AI agents, and orchestration tools.

• Knowledge of vector databases, embeddings, semantic search, and RAG architectures.

• Experience with Docker, Kubernetes, CI/CD, and MLOps practices.

• Familiarity with model monitoring, evaluation frameworks, and AI observability.

• Experience deploying scalable AI services in cloud environments.

• Understanding of AI security, governance, and responsible AI practices.

Ideal Candidate

The ideal candidate combines strong software engineering skills with practical AI experience and can turn emerging AI capabilities into reliable, scalable applications that deliver measurable business value.