Research Development Engineer

2 days ago

Delhi, Delhi, India Red Cloud Computing Pvt Ltd. Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Core Principles:

  • Multi-disciplinary engineers > narrow specialists (I need athletes," not "position players").
  • Self-driven, product-minded people who can explore and execute without hand-holding.
  • Infrastructure + AI hybrid skills

About the Role:

We are building a lean, high-impact R&D team that will shape the future of our AI and software platforms. This team will work directly with the CTO to explore, design, and deliver next-generation solutions across Agentic AI, infrastructure platforms, DevOps, and secure software workloads.

What You'll Do

  • Research, design, and implement Agentic AI systems, LLM pipelines, and hybrid AI workloads.
  • Build and maintain infrastructure platforms (Kubernetes, OpenShift, Linux systems, cloud-native environments).
  • Develop full-stack solutions: APIs, dashboards, integrations, and automation.
  • Establish DevOps/MLOps pipelines for deploying, scaling, and monitoring AI workloads.
  • Implement security and compliance guardrails for infrastructure, data, and AI agents.
  • Collaborate closely with the CTO on strategic R&D initiatives, shaping product direction.
  • Deliver proofs-of-concept rapidly, then harden into production-ready systems.

Who You Are

  • A self-starter who thrives in ambiguous environments and can turn concepts into working software.
  • Comfortable wearing multiple hats: AI engineer, software developer, DevOps engineer, and security-minded architect.
  • Curious and experimental, but disciplined about building robust, secure, and scalable systems.
  • Strong communicator who can work directly with leadership and present technical insights clearly.

Required Skills

  • Software Development: Proficiency in Python, Go, or with experience building APIs and platforms.
  • AI/ML: Hands-on with PyTorch/TensorFlow, HuggingFace, LangChain, or other LLM/agent frameworks.
  • Infrastructure / DevOps: Kubernetes, Docker, Linux administration, CI/CD pipelines (GitHub Actions, Argo, Jenkins, etc.).
  • Cloud Platforms: AWS, Azure, or GCP and on prem Hybrid (infrastructure, storage, IAM).
  • Security Mindset: Understanding of RBAC, IAM, data governance, and secure software development practices.
  • Strong experience building end-to-end systems (from infrastructure to workload).

Nice-to-Have

  • Experience with MLOps tools (Kubeflow, MLflow, Weights & Biases).
  • Exposure to vector databases (FAISS, Pinecone, Weaviate).
  • Knowledge of agentic AI frameworks and orchestration.
  • Contributions to open-source projects.

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