- Company Name
- Indsafri
- Job Title
- AI/ML Engineer
- Job Description
-
**Job Title**
AI/ML Cloud Engineer (AWS + AI/ML)
**Role Summary**
Design, build, and deploy scalable, serverless AI/ML solutions on AWS. Lead end‑to‑end development of Python‑based ML pipelines, integrate LLMs, RAG, and AI Agents into cloud‑native applications, and ensure secure, cost‑effective, high‑performance delivery.
**Expectations**
- Deliver production‑ready AI/ML services on AWS within sprint timelines.
- Collaborate across data science, cloud architecture, and application teams.
- Maintain rigorous security, cost, and performance monitoring.
**Key Responsibilities**
- Architect and implement AWS serverless architectures (Lambda, API Gateway, Step Functions, etc.) for AI workloads.
- Develop Python backends, CI/CD pipelines, and ML deployment workflows.
- Deploy and integrate RAG, AI Agents, and LLM models into cloud applications.
- Optimize infrastructure cost and performance, applying AWS best practices.
- Secure models and data using IAM, VPC, and encryption.
- Monitor, troubleshoot, and iterate on AI/ML systems.
**Required Skills**
- AWS Cloud services: Compute, Storage, Networking, IAM, CloudWatch.
- Serverless design: Lambda, API Gateway, Step Functions, EventBridge.
- Python programming; experience with ML libraries (PyTorch, TensorFlow, Hugging Face).
- AI concepts: Retrieval‑Augmented Generation, AI Agents, LLM integration.
- ML model deployment on AWS (SageMaker, ECS/EKS, Lambda).
- CI/CD pipelines in AWS (CodePipeline, CodeBuild, CloudFormation).
- Security best practices, networking, and cost optimization.
**Preferred Skills**
- Vector databases (Pinecone, Chroma) and embedding model expertise.
- Docker & container orchestration (ECS, EKS).
- Enterprise‑level AI deployments and scalable architecture patterns.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Software Engineering, or related field.
- AWS certifications (e.g., Solutions Architect – Associate/Professional) strong advantage.