Build the AI-First Enterprise.
From the Inside.

WinInfoSoft's AI internship puts final-year and recently graduated engineers into live client projects from week one — not isolated sandbox environments. You will work alongside senior AI engineers on real production problems with enterprise data and systems.

• Assist in building and evaluating RAG pipelines, embedding workflows, and prompt engineering frameworks for enterprise clients
• Run model evaluation experiments, document results, and produce structured reports on accuracy, latency, and failure modes
• Contribute to data preprocessing pipelines that transform unstructured enterprise documents into AI-queryable formats
• Participate in client technical discussions and produce meeting notes and follow-up documentation
• Explore and benchmark open-source AI models (Mistral, Llama, Gemma) for specific enterprise use cases

• Final year of B.Tech/M.Tech in Computer Science, AI, Data Science, or equivalent — or recent graduate
• Strong Python fundamentals; familiarity with pandas, NumPy, and at least one ML framework (PyTorch or scikit-learn)
• Genuine interest in large language models and AI systems beyond theoretical coursework
• Good written communication — you will document your own work
• Able to commit to a minimum 3-month full-time internship on-site in Noida

• Personal projects, Kaggle notebooks, or GitHub repositories demonstrating applied ML or NLP work
• Familiarity with LangChain, Hugging Face, or OpenAI API
• Any prior internship or freelance project involving real data (not toy datasets)

We are looking for a Cybersecurity Engineer to join our managed security and enterprise modernisation practice. You will work across client environments — securing legacy systems during AI modernisation, conducting security assessments, and operating threat detection tooling for enterprise clients across India, Australia, and the Middle East.

• Conduct security assessments and vulnerability scans across client on-premise and cloud environments (AWS, Azure, GCP)
• Implement and manage SIEM, EDR, and threat detection tools; triage alerts and investigate incidents
• Support clients through CERT-In compliance, ISO 27001 audit preparation, and security policy documentation
• Perform penetration testing on web applications, APIs, and network infrastructure under scoped engagement agreements
• Design and review security architecture for AI systems and cloud-native deployments — IAM, secrets management, network segmentation
• Produce clear security reports and remediation roadmaps for non-technical client stakeholders

• 2–5 years in cybersecurity roles with demonstrable hands-on technical experience (not purely GRC/compliance)
• Proficiency in network security concepts, common attack vectors (OWASP Top 10, MITRE ATT&CK), and defensive tooling
• Experience with at least one SIEM platform (Splunk, Microsoft Sentinel, or equivalent)
• Scripting ability in Python or Bash for automation of security workflows
• Familiarity with cloud security posture management across AWS or Azure
• Strong English communication — client security reporting is a core output

• Certifications: CEH, OSCP, CompTIA Security+, or equivalent
• Experience securing AI/ML systems or reviewing LLM deployment security
• Familiarity with Indian regulatory frameworks (CERT-In, DPDP Act, RBI cybersecurity guidelines)

We are expanding our cloud engineering practice and need a Cloud Infrastructure Engineer who can design, deploy, and manage multi-cloud environments for enterprise clients undergoing AI-led modernisation. You will own infrastructure from initial architecture through to production operations and managed service handover.

• Design and deploy multi-cloud infrastructure on AWS, Azure, and GCP — VPC, compute, storage, networking, and IAM
• Build infrastructure-as-code using Terraform and Ansible; maintain reproducible, version-controlled environments
• Set up and manage CI/CD pipelines (GitHub Actions, Azure DevOps, or Jenkins) for application and ML model deployments
• Implement container orchestration on Kubernetes (EKS, AKS, or GKE); manage Helm charts and cluster operations
• Design and monitor cloud cost optimisation strategies; produce monthly cost reports with actionable recommendations for clients
• Support AI/ML workloads — GPU instance configuration, model serving infrastructure, and MLOps pipeline plumbing
• Respond to infrastructure incidents within SLA windows and conduct post-incident reviews

• 3–7 years of cloud infrastructure or DevOps engineering experience across at least two major cloud providers
• Strong Terraform proficiency — you write modules, not just apply templates
• Hands-on Kubernetes experience in production, including troubleshooting cluster-level issues
• Scripting in Python and Bash; comfortable automating repetitive infrastructure tasks
• Solid understanding of networking fundamentals (DNS, load balancing, TLS, VPN, BGP basics)
• Experience setting up observability stacks (Prometheus, Grafana, or cloud-native equivalents)

• Cloud certifications: AWS Solutions Architect, Azure Administrator, or GCP Professional Cloud Architect
• Experience supporting ML infrastructure — SageMaker, Azure ML, Vertex AI, or self-hosted GPU clusters
• Familiarity with FinOps practices and cloud cost governance frameworks