AIML Architect

Good co India; United States; Remote; USD 140,000 - 230,000; Full time

Job summary

Good co India seeks an experienced AI/ML Architect to define scalable, secure architectures and lead end-to-end ML systems. You will drive data ingestion, feature engineering, model training, evaluation, and deployment while optimizing performance and cost.

Responsibilities include overseeing generative AI applications, LLMs, RAG, vector databases, and AI agents, with a strong focus on governance, privacy, and reliability.

Qualifications

• Bachelor’s or higher in CS/AI/IT or related field.
• 5–10 years in software/data science/AI solution roles with architecture leadership.
• Strong Python programming and experience with ML frameworks.
• Experience deploying enterprise AI solutions at scale.

Responsibilities

• Define and lead scalable, secure AI/ML architectures aligned with business goals.
• Design end-to-end ML systems: ingestion, preprocessing, training, deployment, monitoring.
• Develop AI solutions using ML, DL, NLP, and CV tech.
• Architect generative AI apps with LLMs, RAG, vector stores, and AI agents.
• Establish MLOps/LLMOps for automation, versioning, monitoring, lifecycle management.
• Design cloud-native AI solutions on AWS/Azure/GCP and ensure enterprise-grade quality.
• Collaborate with data scientists, engineers, and stakeholders to translate problems to AI solutions.

Skills

AI/ML architecture

MLOps/LLMOps

Python

SQL

TensorFlow

PyTorch

LangChain

RAG

Vector databases

Cloud platforms

Education

Bachelor's degree in CS/AI/IT

Master's degree in AI/ML or related field

Tools

AWS

Azure

GCP

Docker

Kubernetes

MLflow

Job description

Role & responsibilities

• Define and lead the architecture of scalable, secure, and high-performance AI/ML solutions aligned with business objectives.
• Design end-to-end machine learning systems, including data ingestion, preprocessing, feature engineering, model training, evaluation, deployment, and monitoring.
• Develop and implement AI solutions using machine learning, deep learning, natural language processing (NLP), and computer vision technologies.
• Architect generative AI applications using large language models (LLMs), retrieval-augmented generation (RAG), vector databases, and AI agent frameworks.
• Evaluate and select appropriate AI/ML algorithms, frameworks, models, and cloud services based on business requirements and technical feasibility.
• Establish MLOps and LLMOps practices to automate model development, deployment, versioning, monitoring, and lifecycle management.
• Design and implement cloud-native AI/ML solutions using AWS, Microsoft Azure, or Google Cloud Platform.
• Ensure AI solutions meet enterprise requirements for scalability, reliability, performance, security, privacy, and responsible AI practices.
• Optimize model accuracy, inference latency, resource utilization, and infrastructure costs.
• Collaborate with data scientists, data engineers, software developers, product managers, and business stakeholders to translate business problems into AI-driven solutions.
• Establish architectural standards, reusable components, technical guidelines, and best practices for AI/ML development.
• Lead technical reviews, conduct proof-of-concept initiatives, assess emerging AI technologies, and recommend suitable solutions.
• Mentor AI/ML engineers and guide cross-functional teams in delivering production-ready AI applications.
• Monitor model performance, data drift, bias, and system reliability to ensure continuous improvement.

Preferred candidate profile

• Bachelors degree in Computer Science, Artificial Intelligence, Information Technology, Engineering, Mathematics, or a related discipline.
• Master’s degree in AI/ML, Data Science, Computer Science, or a related field is preferred.
• 5 to 10 years of experience in software engineering, data science, machine learning engineering, or AI solution development, with demonstrated architecture and technical leadership experience.
• Strong programming skills in Python and proficiency with SQL, along with hands-on experience in TensorFlow, PyTorch, or Scikit-learn.
• Proven expertise in machine learning, deep learning, model evaluation, feature engineering, and production model deployment.
• Experience with generative AI, LLMs, prompt engineering, RAG, embeddings, vector databases, and frameworks such as LangChain or LangGraph.
• Strong knowledge of MLOps/LLMOps tools and practices, including MLflow, model monitoring, CI/CD, automated testing, and model lifecycle management.
• Hands-on experience with cloud AI/ML services across AWS, Microsoft Azure, or Google Cloud Platform.
• Familiarity with Docker, Kubernetes, REST APIs, microservices, distributed systems, and scalable solution architecture.
• Understanding of AI governance, responsible AI, model explainability, data privacy, security, and regulatory compliance.
• Demonstrated ability to design end-to-end AI solutions, evaluate architectural trade-offs, and deliver measurable business outcomes.
• Strong problem-solving, communication, stakeholder management, mentoring, and technical leadership skills.
• Relevant cloud, AI/ML, or architecture certifications are an advantage.
• Experience deploying enterprise-scale AI applications and optimizing models for performance, reliability, and cost is highly desirable.