Accounts & Finance Head (CA)- garment export

Job Title: AWS Devops Engineer – Manager Business solutions

Location: Gurgaon, India

Experience Required: 8-12 years

Industry: IT

We are looking for a seasoned AWS DevOps Engineer with robust experience in AWS middleware services and MongoDB Cloud Infrastructure Management. The role involves designing, deploying, and maintaining secure, scalable, and high-availability infrastructure, along with developing efficient CI/CD pipelines and automating operational processes.

Key Deliverables (Essential functions & Responsibilities of the Job):

·         Design, deploy, and manage AWS infrastructure, with a focus on middleware services such as API Gateway, Lambda, SQS, SNS, ECS, and EKS.

·         Administer and optimize MongoDB Atlas or equivalent cloud-based MongoDB solutions for high availability, security, and performance.

·         Develop, manage, and enhance CI/CD pipelines using tools like AWS CodePipeline, Jenkins, GitHub Actions, GitLab CI/CD, or Bitbucket Pipelines.

·         Automate infrastructure provisioning using Terraform, AWS CloudFormation, or AWS CDK.

·         Implement monitoring and logging solutions using CloudWatch, Prometheus, Grafana, or the ELK Stack.

·         Enforce cloud security best practices — IAM, VPC setups, encryption, certificate management, and compliance controls.

·         Work closely with development teams to improve application reliability, scalability, and performance.

·         Manage containerized environments using Docker, Kubernetes (EKS), or AWS ECS.

·         Perform MongoDB administration tasks such as backups, performance tuning, indexing, and sharding.

·         Participate in on-call rotations to ensure 24/7 infrastructure availability and quick incident resolution.

Knowledge Skills and Abilities:

·         7+ years of hands-on AWS DevOps experience, especially with middleware services.

·         Strong expertise in MongoDB Atlas or other cloud MongoDB services.

·         Proficiency in Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or AWS CDK.

·         Solid experience with CI/CD tools: Jenkins, CodePipeline, GitHub Actions, GitLab, Bitbucket, etc.

·         Excellent scripting skills in Python, Bash, or PowerShell.

·         Experience in containerization and orchestration: Docker, EKS, ECS.

·         Familiarity with monitoring tools like CloudWatch, ELK, Prometheus, Grafana.

·         Strong understanding of AWS networking and security: IAM, VPC, KMS, Security Groups.

·         Ability to solve complex problems and thrive in a fast-paced environment.

Preferred Qualifications

·         AWS Certified DevOps Engineer – Professional or AWS Solutions Architect – Associate/Professional.

·         MongoDB Certified DBA or Developer.

·         Experience with serverless services like AWS Lambda, Step Functions.

·         Exposure to multi-cloud or hybrid cloud environments.

Mail updated resume with current ctc-

Email: etalenthire[at]gmail[dot]com

Satish; 88 O2 74 97 43

Job Title: Salesforce QA Engineer

Experience: 6+ Years

Location: Bangalore

Work mode: Hybrid (2 days work from office) (Manyata Tech Park)

Job description:

6+ years of hands on experience with both Manual and Automated testing with strong preference of experience using AccelQ on Salesforce ans SAP platforms.

Proven expertise in Salesforce particularly within the Sales Cloud module.

Proficient in writing complex SOQL and SQL queries for data validation and backend testing.

Extensive experience in designing and developing robust, reusable automated test scripts for Salesforce environments.

Highly skilled at early issue detection, with a deep understanding of backend configurations, process flows and validation rules.

Should have a strong background in Salesforce testing, with hands-on experience in automation tools such as Selenium, Provar, or TestNG. 

You will be responsible for creating and maintaining automated test scripts, executing test cases, identifying bugs, and ensuring the quality and reliability of Salesforce applications. 

A solid understanding of Salesforce modules (Sales Cloud, Service Cloud, etc.) and APIs is essential. 

Experience with CI/CD tools like Jenkins and version control systems like Git is preferred. 

You will work closely with developers, business analysts, and stakeholders to define test strategies and improve the overall QA process. 

Minimum 3 years of experience in Sales Cloud is required.

Proficiency in test automation using any tool (AccelQ preferred).

Hands-on experience with API testing.

Strong knowledge of SQL queries.

Manual testing experience with any third-party applications.(SAP, ERP,etc)

Job Title: Chief Engineer: Deep Learning Compiler Expert

You will collaborate with experts in machine learning, algorithms and software to lead our effort of deploying machine learning models onto Samsung Mobile AI platform.

In this position, you will contribute, develop and enhance our compiler infrastructure for high-performance by using open-source technology like MLIR, LLVM, TVM and IREE.

Necessary Skills / Attributes:

• 6 to 15 years of experience in the field of compiler design and graph mapping.
• 2+ years hands-on experience with MLIR and/or LLVM.
• Experience with multiple toolchains, compilers, and Instruction Set Architectures.
• Strong knowledge of resource management, scheduling, code generation, and compute graph optimization.
• Strong expertise in writing modern standards (C++17 or newer) C++ production quality code along test-driven development principles.
• Comfortable and experienced in software development life cycle - coding, debugging, optimization, testing, and continuous integration.
• Familiarity with parallelization techniques for ML acceleration.
• Experience working on and contributing to an active compiler toolchain codebase, such as LLVM, MLIR, or Glow.
• Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, recurrent networks, etc.
• Experience of developing in a mainstream machine-learning framework, e.g. PyTorch, Tensorflow or Caffe.
• Experience operating in a fast-moving environment where the workloads evolve at a rapid pace.
• Understanding of the interplay of hardware and software architectures on future algorithms, programming models and applications.
• Experience developing innovative architectures to extend the state of the art in DL performance and efficiency.
• Experience with Hardware and Software Co-design.

M.S. or higher degree, in CS/CE/EE or equivalent with industry or open-source experience.

Work Profile:

• Design, implement and test compiler features and capabilities related to infrastructure and compiler passes.
• Ingest CNN graphs in Pytorch/TF/TFLite/ONNX format and map them to hardware implementations, model data-flows, create resource utilization cost-benefit analysis and estimate silicon performance.
• Develop graph compiler optimizations (operator fusion, layout optimization, etc) that are customized to each of the different ML accelerators in the system.
• Integrate open-source and vendor compiler technology into Samsung ML internal compiler infrastructure.
• Collaborate with Samsung ML acceleration platform engineers to guide the direction of inferencing and provide requirements and feature requests for hardware vendors.
• Closely follow industry and academic developments in the ML compiler domain and provide performance guidelines and standard methodologies for other ML engineers.
• Create and optimize compiler backend to leverage the full hardware potential, efficiently optimizing them using novel approaches.
• Evaluate code performance, debug, diagnose and drive resolution of compiler and cross-disciplinary system issues.
• Contribute to the development of machine-learning libraries, intermediate representations, export formats and analysis tools.
• Communicate and collaborate effectively with cross-functional hardware and software engineering teams.
• Champion engineering and operational excellence, establishing metrics and processes for regular assessment and improvement.

Keywords to source candidates

Senior Developer, Deep Learning, Prediction engine, Machine Learning, Compiler

As a Senior Software Engineer you have complete ownership of building out the Docexa product along with product people and the rest of the engineering team. This role will act as a great springboard to accelerate career growth & transition into a Tech Lead level role.

Your daily life

• Architecting of the whole platform
• Development of server-side logic
• Building new services and APIs
• Developing core business logic
• Maintenance of current APIs
• Improving the performance and reliability of our systems as we scale

Must-have skills

• You’ve been building web applications professionally for 4+ years
• You’re proficient in PHP 7, Laravel, and PostgreSQL
• You possess strong OOP and design pattern knowledge
• You are familiar with modern technology systems: AWS, load balancers, Kafka queues, caching, etc.
• You write understandable, testable and easy to maintain code
• You’ve the ability to build RESTful APIs
• Explaining complex technical concepts to designers, support team, and fellow engineers is not a problem for you
• Well versed with the fundamentals of computer science and distributed systems

Position: Full Stack developer

Location: Bangalore

Experience:  3 to 5 years, preferably in an agile environment

RESPONSIBILITIES
·     Understanding requirements present in specification documents
·     Knowledge on cloud environment
·     API development for consumption by webapp and mobile apps
·     Database schema design
·     Integration with partner systems based on REST APIs
·     Working with code base across multiple development & staging environments
·     Take part in User Acceptance Testing (UAT)
·     Be part of Production deployment & release activities

TECH SKILLS
·     Must Have:
*       Python and Node Js
*       RDBMS :Postgre SQL/ MongoDB
*       Must have knowledge on AWS or Digital Ocean
*       Good documentation skills
·     Good to have:
*       Javascript
*       RabbitMQ
*       Django
*       Docker
*       Redis
*       Flask
*       nginx
*       graylog