Business Development Manager

Data Engineer  

Overview 

We are seeking skilled Data Engineers to join our Data & Digital Twin Foundation team. You will design, build, and maintain data pipelines that power digital twin platforms, real-time operational systems, and AI/ML workloads. Working closely with data architects, simulation engineers, and ML teams, you will transform raw operational data into high-quality, governed datasets that drive intelligent decision-making. 

Our core data platform stack includes: 

Data Platform & Lakehouse 

• Databricks as the single point of truth for all data
• Realtime Data Pipelines implemented using Kafka for data ingestion.
• Databricks SQL for analytical queries 
• Unity Catalog for metadata management and governance 
• Terradata for data warehouse and business intelligence.

Stream & Event Processing 

• Apache Kafka for real-time event ingestion 
• Structured Streaming for continuous data processing 
• Delta Live Tables for declarative, quality-enforced pipelines  

Data Quality 

• Delta Live Tables expectations for data validation 
• Data profiling and anomaly detection 

Key Responsibilities 

• Design, develop, and maintain scalable data pipelines using Databricks, PySpark, and Delta Lake 
• Build real-time and batch data ingestion pipelines from diverse operational systems using high-performance Kafka data pipelines.
• Implement data transformations that serve digital twin platforms and operational analytics 
• Integrate Kafka event streams with Databricks for real-time operational state updates 
• Implement data quality checks using Delta Live Tables expectations 
• Ensure data governance compliance through Unity Catalog (lineage, access control, metadata) 
• Optimize pipeline performance, reliability, and cost efficiency 
• Write clean, well-documented, and testable code following engineering best practices 
• Collaborate with ML engineers to deliver feature-engineered datasets 
• Participate in code reviews, knowledge sharing, and continuous improvement initiatives 
• Support production data systems through monitoring, troubleshooting, and incident resolution.
• Build business data warehouse solutions using Terradata for business intelligence.

Preferred Qualifications 

• 7+ years of hands-on data engineering experience 
• Track record of building and maintaining production-grade data pipelines 
• Experience with Delta Live Tables for declarative pipeline development 
• Experience working in agile, cross-functional teams 
• Familiarity with time-series data patterns and operational data modelling 

Highly Desirable 

• Experience building data pipelines for digital twin or simulation platforms 
• Familiarity with operational state modeling for real-time systems 
• Exposure to physics-informed or time-series ML feature engineering 
• Experience working with distributed, multidisciplinary teams 
• Exposure to industrial domains such as Manufacturing, Logistics, or Transportation is a plus 

Location: Hyderabad, Telangana 

Department: Engineering 

Employment Type: Full-Time

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 

Assist in content creation for Instagram, Facebook, and other platforms.

Help plan and execute social media campaigns.

Monitor and analyze engagement metrics.

Collaborate with the marketing team on content ideas.

Engage with our community by responding to comments and messages.

Assist with influencer outreach.

Requirements:

Passion for social media and skincare.

Basic knowledge of Instagram, Facebook, TikTok.

Strong communication and organizational skills.

Creativity and a keen eye for design.

Previous experience in social media management is a bonus.

Internship Duration: 3 months with potential for full-time hire.

LogiNext is looking for a technically savvy and passionate Software Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.

In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.

Responsibilities:

Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Requirements:

Bachelors degree or higher in Computer Science, Information Technology, Information Systems, Statistics, Mathematics, Commerce, Engineering, Business Management, Marketing or related field from top-tier school 2 to 3 year experince in in data mining, data modeling, and reporting. Understading of SaaS based products and services. Understanding of machine-learning and operations research Experience of R, SQL and Python; familiarity with Scala, Java or C++ is an asset Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop) Analytical mind and business acumen and problem-solving aptitude Excellent communication and presentation skills Proficiency in Excel for data management and manipulation Experience in statistical modeling techniques and data wrangling Able to work independently and set goals keeping business objectives in mind

Job Summary: 

We are seeking a highly skilled Senior .NET Engineer with extensive database design experience to join our team. As a Senior .NET Engineer, you will be responsible for designing, developing, and maintaining complex software applications using the .NET framework. You will also be responsible for designing and implementing complex database solutions using the EF Core framework that support these applications. 

 Specific Responsibilities and Accountabilities: 

• Design, develop, and maintain software applications using the .NET framework and database solutions using Entity Framework Core 
• Create and maintain data models and schema designs using best practices and industry standards  
• Develop and implement database security measures to protect sensitive data  
• Optimize database performance and ensure data integrity  
• Collaborate with cross-functional teams to define, design, and ship new features  
• Write clean, efficient, and maintainable code that meets specifications  
• Troubleshoot and debug software issues as needed  
• Keep up to date with emerging trends and technologies in software development and database design  
• Participate in code reviews and provide feedback to other developers  

Personal Qualities, Knowledge, Experience and Skills Required: 

• Bachelor's or master's degree in computer science or related field 
• At least 5 years of experience in software development using the .NET framework and database design and development using Entity Framework Core  
• Experience with object-oriented programming (OOP) concepts, design patterns and microservice architecture.  
• Experience with database design, including data modelling and schema design  
• Experience with MySQL Server or other relational database management systems  
• Familiarity with agile development methodologies  
• Excellent problem-solving and analytical skills  
• Ability to work independently and as part of a team  
• Strong communication and interpersonal skills  

Skills and Qualification: 

1. Experience in working MEAN stack / Full Stack platform
2. Front-end developer with knowledge of coding into NODE/EXPRESS, JavaScript, Jquery & its plugins.
3. js/Redux/React-native.
4. Knowledge of different NPM packages (Session, Async etc.).
5. Knowledge of Mongo dB/Mongoose/Nosql.
6. Knowledge of Any one framework (Mean.io/Ionic/Meteor).
7. Experience in Backbone.js or Angular.js is a must.
8. Knowledge of responsive design creation.
   CSS3 / HTML / HTML5.

Roles and responsibilities:

• Proficient in SQL, NoSQL, relational database design and methods for efficiently retrieving data 
• Experience building complex and non-interactive systems batch, distributed, etc.
• Be responsible for the technical design and experience in guiding/mentoring others.
• Strong OOPS knowledge, including experience with design patterns
• Experience with relational databases like MySQL/Oracle
• Experience with enterprise application servers like Tomcat/Weblogic/Websphere.
• Exposure to Web Services SOAP and RESTFUL
• Exposure to Agile/Scrum, TDD, and Continuous Integration tools like Jenkins, Bamboo etc.
• Excellent analytical aptitude and problem solving skills.
• Excellent communication and customer interfacing skill

Responsibilities

• Developing new features and user interfaces from wireframe models
• Ensuring the best performance and user experience of the application
• Fixing bugs and performance problems
• Writing clean, readable, and testable code
• Cooperating with back-end developers, designers, and the rest of the team to deliver well-architected and high-quality solutions

Qualifications

• Desire to work in a startup environment, able to self-manage and work remotely
• Must have built apps on Android and/or iOS apps with Flutter/ React Native/ Xamarin/ Ionic/cordova etc
• Proven working experience in software development
• Working experience in mobile development
• Have published one or more mobile apps in Google Play or App Store
• Experience with third-party libraries and APIs
• Working knowledge of the general mobile landscape, architectures, trends, and emerging technologies
• Solid understanding of the full mobile development life cycle, including automated testing and building
• Experience working in an agile development process
• Be proficient in using version control and continuous integration, with tools such as Git and Jenkins.
• Write clear, maintainable and testable code