Graphic Designer

Job Title : Performance Test Engineer

Experience : 6+ Years

Location : Baner, Pune

Joining : Immediate (by 1st week of October)

Job Summary :

We are seeking a skilled and motivated Performance Test Engineer with a strong background in performance testing, automation, and analysis. The role involves ensuring product excellence through performance tuning, scalability validation, and end-to-end performance engineering.

Mandatory Skills : Performance Testing (JMeter/LoadRunner/RPT), Performance Analysis, Automation Testing, Load & Scalability Testing.

Key Responsibilities :

• Design, develop, and execute performance test plans, scripts, and scenarios using JMeter, LoadRunner, or RPT.
• Conduct load, stress, scalability, and endurance testing for enterprise applications.
• Analyze test results, identify bottlenecks, and provide recommendations for optimization.
• Collaborate with development and architecture teams for detailed performance analysis and tuning.
• Monitor system health, troubleshoot performance issues, and provide technical insights.
• Work on multi-user scenario scripting and cloud-based performance testing.

Requirements :

• 6+ years of experience in software testing, with at least 2 years in automation and 2 years in performance test analysis.
• Hands-on expertise in JMeter, LoadRunner, or RPT.
• Strong understanding of performance engineering concepts: response time, load, scalability, and tuning.
• Experience in analyzing system metrics and identifying performance bottlenecks.
• Exposure to C++ coding is an added advantage.
• Cloud-based application testing experience is a plus.
• Strong problem-solving, troubleshooting, and collaboration skills.

Interview Process :

1. Technical Interview
2. Online Test
3. HR Interview
4. Client Interview

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 

Strong UX / Product Designer profile

Mandatory (Experience 1) - Must have 3+ YOE in UX / Product Design, with a focus towards B2C Products

Mandatory (Experience 2) - Must have recent 2+ YOE in a Good Product Company

Mandatory (Experience 3) - Must have worked on both UX and UI / Visual Designs (some UI / Visual Design experience is required)

Mandatory (Experience 4) - Strong collaboration experience with Product Managers, Researchers, and other Product stakeholders

Mandatory (Portfolio) - Strong portfolio of UX Design and UI/Visual Designs (both are Mandatory) for B2C Products

Mandatory (Company) - Product Company only

Job Summary:

We are looking for technically skilled and customer-oriented SME Voice – Technical Support Associates to provide voice-based support to enterprise clients. The role involves real-time troubleshooting of complex issues across servers, networks, cloud platforms (Azure), databases, and more. Strong communication and problem-solving skills are essential.

Key Responsibilities:

• Provide technical voice support to B2B (enterprise) customers.
• Troubleshoot and resolve issues related to:
• SQL, DNS, VPN, Server Support (Windows/Linux)
• Networking (TCP/IP, routing, firewalls)
• Cloud Services – especially Microsoft Azure
• Application and system-level issues
• Assist with technical configurations and product usage.
• Accurately document cases and escalate unresolved issues.
• Ensure timely resolution while meeting SLAs and quality standards.

Required Skills & Qualifications:

• 2.5 to 5 years in technical support (voice-based, B2B preferred)

 Proficiency in:

• SQL, DNS, VPN, Server Support
• Networking, Microsoft Azure
• Basic understanding of coding/scripting
• Strong troubleshooting and communication skills
• Ability to work in a 24x7 rotational shift environment

1. Screening resumes of the candidates based on the job description available.

2. Shortlisting resumes based on several search factors such as skills, recently updated resume, location, experience, previous employers etc.

3. Calling the shortlisted candidates to know their interest in the job opening.

4. Convincing candidates to attend the interviews.

5. Finalizing the interview schedule and making the interviewer to be available for taking the interview.

6. After the interview share feedback with the candidate.

7. Salary negotiation and follow-up with them till onboarding.

• Experience in corporate training with minimum 3.5 years of experience in Technical training
• Exposure into C#.Net, ASP.NET, MVC-5, SQL database, HTML-5, CSS-3, Javascript, AngularJS.
• Concepts on ASP.Net MVC and Web API, .Net Core, latest version of .Net core.
• Candidate should have good Presentation, verbal & written communication Skills.
• Good to have Microsoft certification on MVC and implementation knowledge on AngularJs. 

About Digichefs

We’ve been reinventing the meaning of digital marketing or rather, advertising in a digital era since 2015. With over 5 years of cumulative marketing experience at the heart of the organization, we enable our clients to grow and meet their business objectives. Our sweet combination of technology, creative communication, and a thought-through execution strategy bolster the marketing vertical in your business center, so that you may focus on the next important item on your list. Let us help you build a recipe for success.

Know more about us:

Check our website http://www.digichefs.com/">www.digichefs.com   

Watch our journey so far  http://digichefs.in/emailer/digichefs/">Play Showreel - A 180 sec. Sneak Peek 

Why Join Digichefs

We are a boutique Digital Marketing Company focused on performance led to creative campaigns. 

A tight team of 40 makes us an ideal fit for any brand looking for a partner who can support their marketing setup or accelerate them in their growth stage. 

With efficient internal processes & subject expertise in digital, we forge as your extended marketing partner.

Direct access to the founders & the core team, flexibility & agility when situations demand so, clean reporting and transparency at every stage, while completely maintaining the security of your confidential data, are some reasons why our clients love us!

Overview:

The Sr. Performance Marketing Analyst is responsible for planning, optimizing, and executing campaigns to meet and surpass the clients’ success metrics while also supporting the team where needed. 

Job Responsibilities.

• Create and set up new paid media campaigns for clients and partners (Primary Google, Facebook, LinkedIn Ad Platforms)
• Support the TL in the development of the paid media strategy
• Research and analyse new market trends and seasonality fluctuations and apply
• learnings to the campaign(s)
• Keep a tight grip on the market and competitor analysis to discover new opportunities and implement relevant changes
• Analyse and use conversion tracking data to further optimise and develop campaigns
• Proficiency in Google Analytics to optimize and improve the campaign performance.
• Prepare analysis for client fortnightly & monthly review meetings
• Ensure day-to-day operations are aligned with campaign strategies and commercial
• goals
• Ensure work is prioritised and implemented based on agreed deadlines
• Contribute to client weekly calls including updating WIP's/Roadmaps or client logs
• Manage day to day client communication along with responding to client requests,  deliverables and priorities.

Requirements:

• Educated to degree level, or equivalent
• Intermediate Microsoft Excel knowledge and skills
• Previous experience in a similar role (Agency Preferable)
• Smart, motivated, results-driven, and analytical individual
• Have the ability to multitask and work well with a team, as well as being able to prioritise tasks in a fast-paced environment along with the ability to accept interruptions as part of the routine