11+ Customer Acquisition Jobs in Chennai | Customer Acquisition Job openings in Chennai

• Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.

• 2 - 4 years  of relevant experience in Data science.
• Preferred education: Bachelor's degree in a technical field or equivalent experience.
• Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
• Experience in risk and credit score domains preferred.

Job Description:

We are seeking a Cloud & AI Platform Engineer to design and operate AI-native infrastructure that supports large-scale machine learning, generative AI, and agentic AI systems. 

This role will focus on building secure, scalable, and automated multi-cloud platforms across AWS, Azure, GCP, and hybrid on-prem environments, enabling teams to deploy LLMs, AI agents, and data-driven applications reliably in production. 

You will work at the intersection of cloud engineering, MLOps, LLMOps, DevOps, and data infrastructure, helping build platforms that support RAG pipelines, vector search, AI model lifecycle management, and AI observability. 

Key Responsibilities

AI & Agentic Infrastructure 

• Design infrastructure to support agentic AI systems, autonomous agents, and multi-agent workflows. 
• Build scalable runtime environments for LLM orchestration frameworks. 
• Enable deployment of AI copilots, assistants, and autonomous decision systems. 

Common frameworks may include: 

• LangChain 
• LlamaIndex 
• AutoGPT 

LLMOps & AI Model Lifecycle 

Design and manage LLMOps pipelines for the full lifecycle of large language models: 

• Model deployment 
• Prompt management 
• Versioning 
• Evaluation and testing 
• Model monitoring 

Integrate with AI platforms such as: 

• Azure Machine Learning 
• Amazon SageMaker 
• Vertex AI 

Retrieval-Augmented Generation (RAG) Infrastructure 

Design and optimize RAG pipelines that integrate enterprise knowledge with LLMs. 

Responsibilities include: 

• Document ingestion pipelines 
• Embedding generation workflows 
• Knowledge indexing 
• Query orchestration 
• Retrieval optimization 
• Support scalable semantic search architectures. 

Vector Database & Knowledge Infrastructure 

Deploy and manage vector databases used for AI applications and semantic retrieval. 

Common technologies include: 

• Pinecone 
• Weaviate 
• Milvus 
• FAISS 

Responsibilities include: 

• Index optimization 
• Query latency tuning 
• Scalable embedding storage 
• Hybrid search architecture 

Multi-Cloud AI Infrastructure 

Design and maintain AI-ready infrastructure across: 

• Amazon Web Services 
• Microsoft Azure 
• Google Cloud Platform 

Key responsibilities include: 

• GPU infrastructure management 
• Distributed training environments 
• Hybrid cloud integrations with on-prem data centers 
• Infrastructure scaling for AI workloads 

Data Platforms & Integration 

• Support deployment and optimization of data lakes, data warehouses, and streaming platforms. 
• Work with data engineering teams to ensure secure and scalable data infrastructure. 

Cloud Architecture & Infrastructure 

• Design and implement scalable multi-cloud infrastructure across Azure, AWS, and Google Cloud. 
• Build hybrid cloud architectures integrating on-premise environments with cloud platforms. 
• Implement high availability, disaster recovery, and auto-scaling architectures for AI workloads. 

DevOps, Platform Engineering & Automation 

Build automated cloud infrastructure using modern DevOps practices. 

Tools may include: 

• Terraform 
• Docker 
• Kubernetes 
• GitHub Actions 

Responsibilities include: 

• Infrastructure as Code (IaC) 
• Automated deployments 
• CI/CD pipelines for AI models and services 
• Platform reliability and scalability 

AI Observability & Monitoring 

Implement observability frameworks to monitor AI systems in production. 

This includes: 

• Model performance monitoring 
• Prompt evaluation 
• Hallucination detection 
• Latency and throughput analysis 
• Cost monitoring for LLM usage 

Tools may include: 

• Arize AI 
• WhyLabs 
• Weights & Biases 

Security, Governance & Responsible AI 

Ensure AI systems follow strong governance and security practices. 

Responsibilities include: 

• Data privacy and compliance 
• Model governance frameworks 
• Secure model deployment 
• Monitoring model bias and drift 
• AI risk management 

Support enterprise frameworks for Responsible AI and AI compliance. 

Data & Security 

• Experience with data lake architectures, distributed storage, and ETL pipelines 
• Knowledge of data security, encryption, IAM, and compliance frameworks 
• Familiarity with AI governance and responsible AI practices 

Required Skills 

Cloud & Infrastructure 

• Strong experience in Azure (must have), AWS or GCP 
• Hybrid and multi-cloud architecture 
• GPU infrastructure management 

DevOps & Automation 

• Kubernetes 
• Docker 
• Terraform 
• CI/CD pipelines 

AI / ML Platforms 

• MLOps pipelines 
• Model deployment 
• Model monitoring 

AI Application Infrastructure 

• Vector databases 
• RAG pipelines 
• LLM orchestration frameworks 

Programming 

Experience in one or more languages: 

• Python 
• Go 
• Java 
• TypeScript 

Preferred Qualifications 

• Experience building AI copilots or autonomous agents 
• Knowledge of distributed model training - Knowledge of GPU infrastructure and distributed training 
• Familiarity with AI evaluation frameworks - Familiarity with model monitoring, drift detection, and AI observability 
• Experience building enterprise AI platforms 

Education & Experience 

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field 
• 4–8+ years experience in cloud infrastructure, DevOps, or platform engineering 
• Experience working in data-driven or AI-focused environments 

What Success Looks Like 

• Reliable ML model deployment pipelines - Reliable infrastructure for LLMs and AI agents, Scalable RAG knowledge platforms 
• Efficient multi-cloud infrastructure management - Fast deployment cycles for AI products 
• Secure and scalable AI-ready cloud platforms 
• Strong automation and governance across cloud and AI systems 

Consultant – Data Entry / Admin Executive

Roles and Responsibilities

• Insert customer and account data by inputting text based and numerical information from source documents within time limits
• Compile, verify accuracy and sort information according to priorities to prepare source data for computer entry
• Review data for deficiencies or errors, correct any incompatibilities if possible and check output
• Research and obtain further information for incomplete documents
• Apply data program techniques and procedures
• Generate reports, store completed work in designated locations and perform backup operations
• Scan documents and print files, when needed
• Keep information confidential
• Manage calls and queries for information and access relevant files
• Comply with data integrity and security policies
• Ensure proper use of office equipment and address any malfunctions

Requirements and skills

• Proven data entry work experience, as a Data Entry Operator or Admin Executive
• Proficient in using MS Excel skills
• Familiarity with administrative duties
• Typing speed and accuracy
• Excellent knowledge of correct spelling, grammar and punctuation
• Attention to detail
• Confidentiality
• Organization skills, with an ability to stay focused on assigned tasks
• Excellent written and oral Communication skills
• Basic Graduation - Additional computer training or certification will be an asset

Roles and Responsibilities
1. Ability to work on diverse backend stack such as Node JS, Java, Express JS
2. Ability to work on diverse frontend stack such as React JS, Angular 6/7/8/9, HTML5, CSS3

3. Ability to deliver quick POC’s using cutting edge technologies.

4. Preparing reports, manuals and other documentation on the status, operation and maintenance of software.

5. Design, develop, and unit test applications in accordance with established standards

6. Developing, refining, and tuning integrations between applications. Analysing and resolving technical and application problems.

7. Ability to debug application.

8. Should have complete knowledge on developing RESTful Services.

9. Should be able to also work in agile development methodology.
10. Work with designated JavaScript framework to design, develop, and debug web applications
11. Can work on Angular and Integrate backend services
12. Work with the team to manage, optimize, and customize multiple web applications
13. Manage end to end module lifecycle management of the product
14. Push and pull codes via Git repository

Competency Requirements

1. Experience in NodeJS, Java and development using AngularJS / ReactJS
2. Experience in front end frameworks such as Angular.js, React.js, Bootstrap, Foundation etc
3. Experience in client/server application development
4. Knowledge of agile development methodologies
5. Knowledge of unit testing theory
6. Knowledge of AWS cloud
7. Experience in Java, Python and Go will be added advantage

DESIRED SKILLS AND EXPERIENCE

 Strong analytical and problem-solving skills

 Ability to work independently, learn quickly and be proactive

 3-5 years overall and at least 1-2 years of hands-on experience in designing and managing DevOps Cloud infrastructure

 Experience must include a combination of:

o Experience working with configuration management tools – Ansible, Chef, Puppet, SaltStack (expertise in at least one tool is a must)

o Ability to write and maintain code in at least one scripting language (Python preferred)

o Practical knowledge of shell scripting

o Cloud knowledge – AWS, VMware vSphere o Good understanding and familiarity with Linux

o Networking knowledge – Firewalls, VPNs, Load Balancers

o Web/Application servers, Nginx, JVM environments

o Virtualization and containers - Xen, KVM, Qemu, Docker, Kubernetes, etc.

o Familiarity with logging systems - Logstash, Elasticsearch, Kibana

o Git, Jenkins, Jira

The candidates should have:

·  Strong knowledge on Windows and Linux OS

·   Experience working in Version Control Systems like git

·  Hands-on experience in tools Docker, SonarQube, Ansible, Kubernetes, ELK.

·  Basic understanding of SQL commands

·  Experience working on Azure Cloud DevOps

The responsibilities and duties section is the most important part of the job description. Please read them below and if interested, do go ahead and apply!

Roles and Responsibilites:

• Manages talent acquisition process, including sourcing, testing, interviewing, hiring and onboarding
• Keeps job descriptions up-to-date, accurate and compliant with relevant federal, state and local laws for all positions
• Develops training and performance management program that ensures all employees are familiar with their job responsibilities, as well as relevant legal and safety requirements
• Creates and updates compensation strategy through market analysis and pay surveys
• Handles investigation and resolution of employee issues, concerns and conflicts
• Ensures all employment practices comply with federal, state and local regulations