Description

You will design, develop, and deploy scalable AI/ML platforms with a focus on Generative AI and large language models.

Responsibilities

• Develop reusable tooling and self-service platforms for enterprise AI solutions.
• Build frameworks to support scalable deployment of GenAI use cases using pre-trained and fine-tuned models.
• Orchestrate containerized workloads using Kubernetes and OpenShift.
• Implement GitOps-based deployment strategies.
• Integrate vector databases for embeddings and retrieval-augmented generation (RAG).
• Lead platform decisions regarding service auth, state management, observability, and reliability.

Required Skills

• 5+ years of software engineering experience with strong application development expertise.
• Proficiency in Python (Flask/FastAPI) or equivalent languages.
• Expertise in Kubernetes (preferably OpenShift) and container packaging.
• Hands-on experience with DevOps and GitOps practices using Jenkins, ArgoCD, Helm, and Kustomize.
• Experience with CI/CD pipelines and JFrog Artifactory.
• Familiarity with data platforms including SQL/NoSQL, Kafka, and Redis.
• Knowledge of OAuth2.0, security standards, and secure software development lifecycles.
• Understanding of Machine Learning/Deep Learning using frameworks like TensorFlow or PyTorch.
• Experience with multiprocessing, multithreading, async I/O, and performance tuning.
• Bachelor's or Master's degree in Computer Science, AI/ML, or a related field.

Preferred Skills

• Hands-on experience with LLMs (GPT, LLaMA, HuggingFace) and model fine-tuning.
• Experience building AI agents and implementing Agentic Orchestration using Langchain or LangGraph.
• Understanding of ModelOps, LLMOps, and MLOps pipelines.

Key Skills

Education

Bachelor's or Master's degrees