Senior AWS DevOps & Cloud Engineer

Job Summary

Senior AI Python Technical Lead. We are looking for an experienced Senior AI Python Technical Lead to lead the design, architecture, and delivery of enterprise-scale AI, Generative AI, and cloud-native solutions.

Responsibilities

• Lead and mentor AI Engineers, Python Developers, ML Engineers, Data Engineers, MLOps Engineers, Cloud Engineers, and Solution Architects.
• Own technical architecture, technology strategy, engineering standards, and solution delivery.
• Drive AI innovation, PoCs, reusable frameworks, enterprise AI adoption, and platform modernization.
• Engage with business stakeholders and lead cross-functional teams to deliver scalable, secure, and high-performing AI solutions.
• Establish engineering best practices across AI, software engineering, DevOps, cloud, and MLOps.

Requirements

• Bachelor's or Master's degree in computer science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering or a related discipline.
• At least 10 years of hands-on experience in Python software engineering and enterprise application development.
• At least 5 years of experience designing, developing and deploying production-grade AI/ML and Generative AI solutions.
• At least 3 years of experience architecting Retrieval-Augmented Generation (RAG), Agentic AI and enterprise AI platforms.
• Proven experience leading technical teams as a Technical Lead, AI Engineering Manager, Principal Engineer or Solution Architect.
• Experience delivering enterprise AI platforms on AWS or other major cloud providers.
• Strong experience in stakeholder management, engineering governance, solution architecture and large-scale Agile delivery.

Technical Skills

• Programming Backend. Python, SQL, NoSQL.
• FastAPI, Flask, Django.
• REST APIs, GraphQL, Microservices, Distributed Systems.
• AI / Machine Learning. PyTorch, TensorFlow, Scikit-learn.
• Hugging Face Transformers.
• LangChain, LlamaIndex, DSPy.
• Generative AI. LLMs, RAG, GraphRAG.
• AI Agents, Multi-Agent Systems.
• Prompt Engineering, Context Engineering.
• Embeddings, Semantic Search, Hybrid Search.
• Agent Frameworks. LangGraph.
• CrewAI.
• Microsoft AutoGen.
• LangChain Agents.
• Vector Databases. Pinecone, Qdrant, Weaviate.
• ChromaDB, Milvus, FAISS.
• LLMOps Evaluation. LangSmith, Ragas, DeepEval.
• OpenAI Evals, MLflow.
• Model Monitoring, Prompt Lifecycle Management, AI Observability.
• AI Security Governance.
• NeMo Guardrails, Llama Guard, Amazon Bedrock Guardrails.
• Prompt Injection Protection, PII Protection, Responsible AI, AI Governance.
• Cloud AI Platforms. AWS Bedrock, SageMaker.
• ECS, EKS, Lambda, API Gateway.
• EC2, S3, DynamoDB, OpenSearch.
• EventBridge, Step Functions, CloudWatch, IAM.
• DevOps MLOps.
• Docker, Kubernetes.
• Terraform, Jenkins.
• GitHub Actions, ArgoCD.
• CI/CD, GitOps, Model Deployment, Infrastructure as Code.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.