The AI Engineer will design, develop, and deploy advanced, production-ready AI solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, agentic AI workflows, and intelligent automation technologies.
Compensation
₹15,00,000 – ₹22,00,000 per year (15–22 LPA), commensurate with experience and technical expertise
Responsibilities
Design, develop, and deploy AI systems, including LLMs, RAG, agentic workflows, and ML/DL solutions.
Select appropriate models and architectures while balancing accuracy, latency, cost, and complexity.
Train and fine-tune models using PyTorch or Keras, including data preparation and evaluation.
Implement and benchmark research methods before adoption.
Build APIs, inference pipelines, and backend integrations.
Build privacy and anonymization systems for an AI infrastructure team, helping make sensitive real-world data safe and useful for model training.
Compensation
Base salary: $130,000 to $225,000 annually.
Responsibilities
Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information, and choose transformations suited to each data type and use case.
Develop and benchmark detection methods combining rules, statistical models, classifiers, and LLM-based approaches.
Create production pipelines that anonymize raw data before downstream processing, training, evaluation, or synthetic data generation.
Build evaluation frameworks for privacy risk and retained utility, including recall-weighted metrics, leakage tests, and adversarial re-identification attempts.
Design robust systems for new data sources, schema drift, unusual formats, and sensitive information in unexpected fields.
Bright Vision Technologies is seeking a Natural Language Processing Engineer to develop language-processing solutions for extracting, classifying, searching, and interpreting text. The role will prepare text datasets, build and evaluate NLP models, develop production inference services, and collaborate with application and data teams to integrate language intelligence into enterprise workflows.
Locations (2)
Irving, Texas, United States
Las Colinas, Texas, United States
Compensation
$115,000–$165,000 Annually
Responsibilities
Develop NLP pipelines for text classification, entity extraction, semantic search, summarization, or language understanding.
Prepare and label text datasets, normalize content, and implement appropriate preprocessing and feature strategies.
Train, fine-tune, or adapt language models and evaluate results using task-appropriate metrics.
Build inference APIs or batch processing components and integrate them with enterprise applications.
Monitor model quality, analyze errors, and document performance, limitations, and improvement opportunities.
This role is responsible for designing, developing, and supporting AI-powered applications and automation solutions that improve business operations. It combines hands-on programming, cloud, and infrastructure experience with expertise in AI and RPA to deliver reliable, scalable solutions.
Responsibilities
Designs and develops AI applications, intelligent agents, RPA bots, and end-to-end automation workflows.
Translates business requirements into technical designs, reusable components, and maintainable code.
Implements solutions using generative AI, document understanding, information extraction, and business rules.
Integrates solutions with enterprise applications, APIs, databases, and other data sources.
Develops workflows that handle complex scenarios, exceptions, and appropriate human review.
Responsible for designing, developing, and supporting AI-powered applications and automation solutions to improve business operations using programming, cloud, infrastructure, AI, and RPA.
Responsibilities
Designs and develops AI applications, intelligent agents, RPA bots, and end-to-end automation workflows.
Translates business requirements into technical designs, reusable components, and maintainable code.
Implements solutions using generative AI, document understanding, information extraction, and business rules.
Integrates solutions with enterprise applications, APIs, databases, and other data sources.
Develops workflows that handle complex scenarios, exceptions, and appropriate human review.
Requirements
Degree in Computer Science, Engineering, Information Systems, or a related discipline
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