Artificial Intelligence Engineer

Amantya Technologies, Inc.; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Amantya Technologies, Inc. seeks a seasoned AI/ML Architect to lead cross-functional teams and integrate GenAI with traditional ML into enterprise applications. You will oversee end-to-end AI solution development from problem framing to deployment and monitoring.

The role demands deep expertise in Python, ML frameworks, containerization, microservices, and strong communication skills to engage customers and stakeholders, ensuring scalable, explainable models and robust data flows.

Qualifications

• Solid foundation in software engineering and AI/ML technologies.
• Proven track record delivering scalable AI solutions in enterprise settings.
• Experience architecting and deploying AI solutions across full lifecycle.

Responsibilities

• Technical Leadership: mentor AI developers and ensure scalable, secure designs.
• AI Application Development: architect and oversee end-to-end AI app lifecycle, optimize models and address drift.
• Architectural Oversight: define data flow, model integration, and API development.
• Customer Engagement: communicate architecture decisions to stakeholders and ensure proper documentation and timelines.

Skills

GenAI & LLMs

Fine-tuning LLMs

Text generation

Summarization

Translation

Conversational AI

Classification

Regression

Clustering

Time-series

TensorFlow

PyTorch

Transformers

scikit-learn

Keras

MLflow

Kubeflow

TensorFlow Extended

Docker

Kubernetes

Serverless

API development

Education

Bachelor's or Master's in CS/AI/DS

Tools

TensorFlow

PyTorch

Hugging Face Transformers

scikit-learn

Keras

MLflow

Kubeflow

TFX

Docker

Kubernetes

Job description

The ideal candidate will have a solid foundation in software engineering, AI/ML technologies, and software development processes.

Required AI/ML Skills:

• Generative AI (GenAI): Experience with Large Language Models (LLMs) like GPT, BERT, or LLaMA. Familiarity with fine-tuning LLMs and integrating them into enterprise applications and Databases. Knowledge of text generation, summarization, translation, and conversational AI.


• Traditional Machine Learning: Proficiency in ML techniques like supervised learning, unsupervised learning, and reinforcement learning. Hands-on experience with classification, regression, clustering, and time-series forecasting.


• AI Frameworks and Tools: Proficient in frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn, and Keras. Familiarity with ML pipelines using tools like MLflow, Kubeflow, or TensorFlow Extended (TFX).


• Deployment: Knowledge of containerization (Docker, Kubernetes) and serverless architectures for scalable AI solutions.

Required Software Engineering Skills:

• Programming Languages: Strong proficiency in Python (preferred), Java, or Go for AI application development. Experience with API development frameworks such as FastAPI, Django, or Flask.


• Architectural Concepts: Deep understanding of microservices architecture, event-driven design, and RESTful APIs. Knowledge of distributed systems and high-performance computing.

Soft Skills:

• Communication and Presentation: Excellent verbal and written communication skills, with the ability to simplify complex technical concepts for diverse audiences. Strong presentation skills to effectively convey architectural designs and project updates to customers and stakeholders.


• Team Collaboration: Proven experience in leading and mentoring technical teams, fostering collaboration, and encouraging continuous learning. Ability to work effectively across cross-functional teams including data engineers, product managers, and QA engineers.

Key Responsibilities:

• Technical Leadership: Lead, mentor, and guide a team of AI developers. Ensure adherence to best practices in software engineering, AI model development, and deployment. Review and approve architectural designs, ensuring scalability, performance, and security.


• AI Application Development: o Architect and design AI solutions that integrate both Generative AI (GenAI) and traditional Machine Learning (ML) models. Oversee the end-to-end development lifecycle of AI applications, from problem definition to deployment and maintenance. Optimize model performance, ensure model explainability, and address model drift issues.


• Architectural Oversight: Develop and present the big-picture architecture of AI applications, including data flow, model integration, and user interaction. Dive deep into individual components, such as data ingestion, feature engineering, model training, and API development. Ensure the AI solutions align with enterprise architectural standards and customer requirements.


• Customer Engagement: Act as the primary technical interface for customer meetings, providing clear explanations of the AI solutions architecture, design decisions, and project progress. Collaborate with stakeholders to understand business needs and translate them into technical requirements. Ensure proper documentation, including design documents, code reviews, and testing protocols. Monitor project timelines and deliverables, ensuring high-quality outcomes.

Qualifications:

• Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field.


• Proven track record of delivering scalable AI solutions in an enterprise setting