119 AI Architect jobs in Coimbatore

• Position : AI Architect -PERMANENT Only
• Experience : 9+ years (Relevant 8 years is a must)
• Budget : Up to ₹40–45 LPA
• Notice Period : Immediate to 45 days
• Key Skills : Python, Data Science (AI/ML), SQL
• Location - TVM/Kochi/remote

Job Purpose

Responsible for consulting for the client to understand their AI/ML, analytics needs & delivering AI/ML

applications to the client.

Job Description / Duties & Responsibilities

▪ Work closely with internal BU’s and business partners (clients) to understand their business problems and

translate them into data science problems

▪ Design intelligent data science solutions that delivers incremental value the end stakeholders

▪ Work closely with data engineering team in identifying relevant data and pre-processing the data to suitable

models

▪ Develop the designed solutions into statistical machine learning models, AI models using suitable tools and

frameworks

▪ Work closely with the business intelligence team to build BI system and visualizations that delivers the

insights of the underlying data science model in most intuitive ways possible.

▪ Work closely with application team to deliver AI/ML solutions as microservices

Job Specification / Skills and Competencies

▪ Masters/Bachelor’s in Computer Science or Statistics or Economics

▪ At least 6 years of experience working in Data Science field and is passionate about numbers, quantitative

problems

▪ Deep understanding of Machine Learning models and algorithms

▪ Experience in analysing complex business problems, translating it into data science problems and modelling

data science solutions for the same

▪ Understanding of and experience in one or more of the following Machine Learning algorithms:-Regression ,

Time Series

▪ Logistic Regression, Naive Bayes, kNN, SVM, Decision Trees, Random Forest, k-Means Clustering etc.

▪ NLP, Text Mining, LLM (GPTs)

▪ Deep Learning, Reinforcement learning algorithm

▪ Understanding of and experience in one or more of the machine learning frameworks -TensorFlow, Caffe,

Torch etc.

▪ Understanding of and experience of building machine learning models using various packages in one or more

of the programming languages– Python / R

▪ Knowledge & Experience on SQL, Relational Databases, No SQL Databases and Datawarehouse concepts

▪ Understanding of AWS/Azure Cloud architecture

▪ Understanding on the deployment architectures of AI/ML models (Flask, Azure function, AWS lambda)

▪ Knowledge on any BI and visualization tools is add-on (Tableau/PowerBI/Qlik/Plotly etc).

▪To adhere to the Information Security Management policies and procedures.

Soft Skills Required

▪ Must be a good team player with good communication skills

▪ Must have good presentation skills

▪ Must be a pro-active problem solver and a leader by self

▪ Manage & nurture a team of data scientists

▪ Desire for numbers and patterns

We are seeking a highly skilled and experienced AWS Architect with a strong background in Data Engineering and expertise in Generative AI. In this pivotal role, you will be responsible for designing, building, and optimizing scalable, secure, and cost-effective data solutions that leverage the power of AWS services, with a particular focus on integrating and managing Generative AI capabilities. The ideal candidate will possess a deep understanding of data architecture principles, big data technologies, and the latest advancements in Generative AI, including Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). You will work closely with data scientists, machine learning engineers, and business stakeholders to translate complex requirements into robust and innovative solutions on the AWS platform.

Responsibilities:

• Architect and Design: Lead the design and architecture of end-to-end data platforms and pipelines on AWS, incorporating best practices for scalability, reliability, security, and cost optimization.

• Generative AI Integration: Architect and implement Generative AI solutions using AWS services like Amazon Bedrock, Amazon SageMaker, Amazon Q, and other relevant technologies. This includes designing RAG architectures, prompt engineering strategies, and fine-tuning models with proprietary data (knowledge base).

• Data Engineering Expertise: Design, build, and optimize ETL/ELT processes for large-scale data ingestion, transformation, and storage using AWS services such as AWS Glue, Amazon S3, Amazon Redshift, Amazon Athena, Amazon EKS and Amazon EMR.

• Data Analytics: Design, build, and optimize analytical solutions for large-scale data ingestion, analytics and insights using AWS services such as AWS Quicksight

• Data Governance and Security: Implement robust data governance, data quality, and security measures, ensuring compliance with relevant regulations and industry best practices for both traditional data and Generative AI applications.

• Performance Optimization: Identify and resolve performance bottlenecks in data pipelines and Generative AI workloads, ensuring efficient resource utilization and optimal response times.

• Technical Leadership: Act as a subject matter expert and provide technical guidance to data engineers, data scientists, and other team members. Mentor and educate on AWS data and Generative AI best practices.

• Collaboration: Work closely with cross-functional teams, including product owners, data scientists, and business analysts, to understand requirements and deliver impactful solutions.

• Innovation and Research: Stay up-to-date with the latest AWS services, data engineering trends, and advancements in Generative AI, evaluating and recommending new technologies to enhance our capabilities.

• Documentation: Create comprehensive technical documentation, including architectural diagrams, design specifications, and operational procedures.

• Cost Management: Monitor and optimize AWS infrastructure costs related to data and Generative AI workloads.

Required Skills and Qualifications:

• 12+ years of experience in data engineering, data warehousing, or big data architecture.

• 5+ years of experience in an AWS Architect role, specifically with a focus on data.

• Proven experience designing and implementing scalable data solutions on AWS.

• Strong hands-on experience with core AWS data services, including:

o Data Storage: Amazon S3, Amazon Redshift, Amazon DynamoDB, Amazon RDS

o Data Processing: AWS Glue, Amazon EMR, Amazon EKS, AWS Lambda, Informatica

o Data Analytic: Amazon Quicksight, Amazon Athena, Tableau

o Data Streaming: Amazon Kinesis, AWS MSK

o Data Lake: AWS Lake Formation

• Strong competencies in Generative AI, including:

o Experience with Large Language Models (LLMs) and Foundation Models (FMs).

o Hands-on experience with Amazon Bedrock (including model customization, agents, and orchestrations).

o Understanding and experience with Retrieval Augmented Generation (RAG) architectures and vector databases (e.g., Amazon OpenSearch Service for vector indexing).

o Experience with prompt engineering and optimizing model responses.

o Familiarity with Amazon SageMaker for building, training, and deploying custom ML/Generative AI models.

o Knowledge of Amazon Q for business-specific Generative AI applications.

• Proficiency in programming languages such as Python (essential), SQL, and potentially Scala or Java.

• Experience with MLOps/GenAIOps principles and tools for deploying and managing Generative AI models in production.

• Solid understanding of data modeling, data warehousing concepts, and data lake architectures.

• Experience with CI/CD pipelines and DevOps practices on AWS.

• Excellent communication, interpersonal, and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.

• Strong problem-solving and analytical abilities.

Preferred Qualifications:

• AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer – Associate/Specialty.

• Experience with other Generative AI frameworks (e.g., LangChain) or open-source LLMs.

• Familiarity with containerization technologies like Docker and Kubernetes (Amazon EKS).

• Experience with data transformation tools like Informatica, Matillion

• Experience with data visualization tools (e.g., Amazon QuickSight, Tableau, Power BI).

• Knowledge of data governance tools like Amazon DataZone.

• Experience in a highly regulated industry (e.g., Financial Services, Healthcare).

We are seeking a highly skilled and experienced AWS Architect with a strong background in Data Engineering and expertise in Generative AI. In this pivotal role, you will be responsible for designing, building, and optimizing scalable, secure, and cost-effective data solutions that leverage the power of AWS services, with a particular focus on integrating and managing Generative AI capabilities. The ideal candidate will possess a deep understanding of data architecture principles, big data technologies, and the latest advancements in Generative AI, including Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). You will work closely with data scientists, machine learning engineers, and business stakeholders to translate complex requirements into robust and innovative solutions on the AWS platform.

Responsibilities:

• Architect and Design: Lead the design and architecture of end-to-end data platforms and pipelines on AWS, incorporating best practices for scalability, reliability, security, and cost optimization.

• Generative AI Integration: Architect and implement Generative AI solutions using AWS services like Amazon Bedrock, Amazon SageMaker, Amazon Q, and other relevant technologies. This includes designing RAG architectures, prompt engineering strategies, and fine-tuning models with proprietary data (knowledge base).

• Data Engineering Expertise: Design, build, and optimize ETL/ELT processes for large-scale data ingestion, transformation, and storage using AWS services such as AWS Glue, Amazon S3, Amazon Redshift, Amazon Athena, Amazon EKS and Amazon EMR.

• Data Analytics: Design, build, and optimize analytical solutions for large-scale data ingestion, analytics and insights using AWS services such as AWS Quicksight

• Data Governance and Security: Implement robust data governance, data quality, and security measures, ensuring compliance with relevant regulations and industry best practices for both traditional data and Generative AI applications.

• Performance Optimization: Identify and resolve performance bottlenecks in data pipelines and Generative AI workloads, ensuring efficient resource utilization and optimal response times.

• Technical Leadership: Act as a subject matter expert and provide technical guidance to data engineers, data scientists, and other team members. Mentor and educate on AWS data and Generative AI best practices.

• Collaboration: Work closely with cross-functional teams, including product owners, data scientists, and business analysts, to understand requirements and deliver impactful solutions.

• Innovation and Research: Stay up-to-date with the latest AWS services, data engineering trends, and advancements in Generative AI, evaluating and recommending new technologies to enhance our capabilities.

• Documentation: Create comprehensive technical documentation, including architectural diagrams, design specifications, and operational procedures.

• Cost Management: Monitor and optimize AWS infrastructure costs related to data and Generative AI workloads.

Required Skills and Qualifications:

• 12+ years of experience in data engineering, data warehousing, or big data architecture.

• 5+ years of experience in an AWS Architect role, specifically with a focus on data.

• Proven experience designing and implementing scalable data solutions on AWS.

• Strong hands-on experience with core AWS data services, including:

o Data Storage: Amazon S3, Amazon Redshift, Amazon DynamoDB, Amazon RDS

o Data Processing: AWS Glue, Amazon EMR, Amazon EKS, AWS Lambda, Informatica

o Data Analytic: Amazon Quicksight, Amazon Athena, Tableau

o Data Streaming: Amazon Kinesis, AWS MSK

o Data Lake: AWS Lake Formation

• Strong competencies in Generative AI, including:

o Experience with Large Language Models (LLMs) and Foundation Models (FMs).

o Hands-on experience with Amazon Bedrock (including model customization, agents, and orchestrations).

o Understanding and experience with Retrieval Augmented Generation (RAG) architectures and vector databases (e.g., Amazon OpenSearch Service for vector indexing).

o Experience with prompt engineering and optimizing model responses.

o Familiarity with Amazon SageMaker for building, training, and deploying custom ML/Generative AI models.

o Knowledge of Amazon Q for business-specific Generative AI applications.

• Proficiency in programming languages such as Python (essential), SQL, and potentially Scala or Java.

• Experience with MLOps/GenAIOps principles and tools for deploying and managing Generative AI models in production.

• Solid understanding of data modeling, data warehousing concepts, and data lake architectures.

• Experience with CI/CD pipelines and DevOps practices on AWS.

• Excellent communication, interpersonal, and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.

• Strong problem-solving and analytical abilities.

Preferred Qualifications:

• AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer – Associate/Specialty.

• Experience with other Generative AI frameworks (e.g., LangChain) or open-source LLMs.

• Familiarity with containerization technologies like Docker and Kubernetes (Amazon EKS).

• Experience with data transformation tools like Informatica, Matillion

• Experience with data visualization tools (e.g., Amazon QuickSight, Tableau, Power BI).

• Knowledge of data governance tools like Amazon DataZone.

• Experience in a highly regulated industry (e.g., Financial Services, Healthcare).

Greetings from TATA Consultancy Services!

We are Looking for Gen AI Architect

Experience: 10-20 Years

Work Location: Pan India

Job Description:

Must Have- Gen AI / LLM /Agentic AI

• Gen AI
• Experience in LLMs, Embedding Models, Prompt Engineering
• Knowledge of statistical programming languages like Python
• Good applied statistical skills
• Good knowledge of machine learning algorithms
• Proficiency in handling imperfections in data & generating insights and patterns.
• Experience with Data Visualization Tools
• Fine tuning of LLM
• Evaluation Framework (RAGAS, ROUGE, BLUE Scrore)
• Autoencoding model (Encoder: ROBERTA/ BERT/ DistilBERT)
• Langsmith framework
• Autoregressive model (Decoder: GPT/ BLOOM/ LLama/ Mistral/ Claude/ CodeGen/ OPT/ PaLM
• RAG/Multimodal Architecture using Langchain/ LlamIndex
• MCP Architecture
• Experience Agentic AI Framework ( Crew AI, AutoGen, LangGraph, Google AVD etc. )
• Experience in Model deployment, LLMOps, Scalability and Performance
• Fine tuning of LLM
• AI ML exp.
• Candidate has exp. in Transformer Architecture (Encoder and decoders)
• Knowledge Graph implementation (If anyone has created knowledge graph, that's good)

Greetings!

TCS is hiring.

Role: Cloud AI Architect (AWS/AZURE/Google)

EXP: 10-16 YEARS

LOCATION: Pan India

Must Have-

• Deep knowledge of AI/ML frameworks (TensorFlow, PyTorch, scikit-learn) integrated with cloud platforms.
• Proficient with cloud AI services:Azure AI (Cognitive Services, ML Studio), AWS AI/ML (SageMaker, Rekognition), Google AI Platform.
• Experience with MLOps tools (Kubeflow, MLflow, Azure MLOps).
• Strong programming skills in Python, R, or Java.
• Understanding of data engineering concepts and cloud data platforms.
• Familiarity with cloud security standards and data privacy regulations.
• Excellent leadership and stakeholder management skills.
• Designing AI-powered cloud infrastructures: This includes selecting appropriate cloud services, designing the architecture, and ensuring scalability and performance.

Experience: 12+ Yrs

Location : Bangalore/Hyderabad (Currently Remote)

Notice Period : Immediate to 20 Days

Key Responsibilities:

Platform & Application Modernization:

• Architect end-to-end modernization solutions across infrastructure, applications, and data on GCP.
• Design cloud-native platforms using GCP services (GKE, Cloud Run, App Engine, Cloud Functions, etc.).
• Lead migration strategies for legacy monoliths to microservices and event-driven architectures.
• Implement DevSecOps, GitOps, and SRE practices using Cloud Build, Terraform, Anthos, and Monitoring.

GenAI Strategy & Implementation:

• Lead the design and implementation of GenAI use cases including intelligent agents, content generation, summarization, and insight extraction.
• Work with state-of-the-art GenAI techniques, including Large Language Models (LLMs), Multi-Modal models, and Large Vision Models, and apply GenAI-related concepts like language modelling and computer vision.
• Utilize Google Cloud’s GenAI ecosystem (Vertex AI, PaLM, Gemini, Model Garden, AutoML) for model development, integration, and fine-tuning.
• Build robust ML infrastructure, covering model deployment, evaluation, optimization, data processing, and debugging in production environments.
• Design and enforce responsible AI frameworks to ensure ethical and secure usage of generative models.

Practice Development:

• Define modernization and GenAI accelerators, frameworks, and reusable assets.
• Mentor teams on modern architecture patterns and GenAI integration best practices.
• Participate in client workshops, RFPs, PoCs, and executive briefings.
• Stay up to date with evolving GCP and GenAI landscapes and drive continuous innovation.

Required Skills & Qualifications:

• Bachelor’s or Master’s in Computer Science, Engineering, or equivalent.
• 12+ years in software/platform architecture, 3–5 years of GCP experience.
• 3 years of experience with state-of-the-art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Strong expertise in GCP services: GKE, Big Query, Cloud Functions, Pub/Sub, Fire store, and Cloud Spanner.
• Hands-on experience with app modernization (Java, .NET, Python) and containerization.
• Experience with data pipelines, model training, fine-tuning, and vector search (e.g., FAISS, Pinecone).
• GCP Professional Cloud Architect or Vertex AI certification preferred.

Nice to Have:

• Experience with LangChain, Weaviate, RAG patterns, and integration of GenAI into business apps.
• Knowledge of Apigee, Istio, service mesh, and multi-cloud environments.
• Familiarity with industry-specific GenAI use cases (e.g., healthcare, finance, retail).
• Contributions to open-source or GenAI communities.

LTIMIndtree is seeking a AI Assurance Architects for our Quality Engineering team in Bangalore.

AI Expertise

In-depth understanding of artificial intelligence, machine learning, and deep learning concepts.

Knowledge of various AI frameworks, libraries, and tools (e.g., TensorFlow, PyTorch).

Testing Methodologies

Proficiency in designing and implementing testing methodologies specific to AI models and algorithms.

Experience in testing different types of AI models, including supervised and unsupervised learning.

Data Quality Assurance

Expertise in assessing and ensuring the quality of training data for AI models.

Familiarity with data preprocessing and cleaning techniques to enhance model performance.

Automation and Tooling

Strong skills in developing automation scripts using any of the Open-source tools for AI applications.

Familiarity with specialized AI testing tools and frameworks.

Performance and Scalability Testing

Experience in assessing and optimizing the performance and scalability of AI models.

Ability to simulate various scenarios to evaluate AI model behaviour under different conditions.

Ethical AI Practices

Knowledge of ethical considerations in AI and the ability to implement testing practices that align with responsible AI principles.

Collaboration

Effective collaboration with senior stakeholders, cross-functional teams.

Regulatory Compliance

Awareness of regulations and standards related to AI, ensuring testing practices comply with relevant guidelines.

Problem-Solving Skills

Strong analytical and problem-solving abilities to identify and address challenges in AI testing.

Team Building

Experience of building technology testing capability from scratch.

LTIMindtree is proud to be an equal opportunity employer. We are committed to equal employment opportunity regardless of race, ethnicity, nationality, gender, gender-identity, gender expression, language, age, sexual orientation, religion, marital status, veteran status, socio-economic status, dis-ability or any other characteristic protected by applicable law.