The Role
Build and operate production Generative AI systems, including RAG pipelines, AI agent workflows, LLM integrations, and Python backend services. Deploy cloud-native applications using AWS, Kubernetes, Terraform, Helm, and CI/CD. Monitor, debug, test, and improve production systems while mentoring through code reviews and owning end-to-end technical delivery.
Summary Generated by Built In
We're looking for a hands-on AI Engineer who combines strong backend engineering fundamentals with hands-on experience building production Generative AI systems. You'll design and ship RAG pipelines, integrate LLMs into real products, and build the backend services that support them, writing code daily, not just architecting on paper.
This is a purely technical IC role, not a managerial one. You’ll lead by example, mentor through code reviews, and own end-to-end technical delivery.
What You’ll Do
- Build and maintain RAG systems, including retrieval, re-ranking, embeddings, and vector databases.
- Build AI agent workflows using LangChain, LangGraph, LlamaIndex, AutoGen, or similar tools.
- Develop backend services and APIs using Python, including async programming and multithreading.
- Deploy and manage AI applications using AWS, Kubernetes, Terraform, Helm, and CI/CD.
- Build event-driven systems using services such as Lambda, SQS, SNS, S3, and CloudWatch.
- Work with tools such as API Gateway, LiteLLM, AWS Bedrock, and SageMaker.
- Monitor, debug, test, and improve AI systems running in production.
What We’re Looking For
Must-Have
- Around 5+ years of experience, with strong backend development.
- Strong Python and software engineering fundamentals.
- Proven experience building and running production systems, not just PoCs.
- Hands-on experience with RAG, embeddings, retrieval, re-ranking, and vector databases.
- Experience with LangChain, LangGraph, LlamaIndex, AutoGen, or similar frameworks.
- Experience with AWS and cloud-native technologies, including Terraform, Kubernetes, Helm, and CI/CD.
- Experience with AWS Bedrock or SageMaker.
- Experience with document/OCR pipelines or PyTorch.
- Experience with AI evaluation, hallucination detection, monitoring, or LLMOps.
What We Value
- Builder mindset: Enjoys writing, debugging, and improving production code.
- Ownership: Takes solutions from development through production.
- Collaboration: Works effectively across backend, data, and platform teams.
- Clear communication: Explains technical decisions clearly.
About
Emumba is a global engineering and consulting company with strengths in software development and an established AWS cloud practice focused on Data and GenAI. For 15 years, our teams across the US, the UAE, and Pakistan have earned trust through quality delivery and ownership of work. We look for people who value the culture they work in as much as the craft they bring to it.
Skills Required
- Around 5 or more years of experience with strong backend development
- Strong Python and software engineering fundamentals
- Proven experience building and operating production systems, not just proof-of-concept systems
- Hands-on experience with RAG, embeddings, retrieval, re-ranking, and vector databases
- Experience with LangChain, LangGraph, LlamaIndex, AutoGen, or similar frameworks
- Experience with AWS and cloud-native technologies, including Terraform, Kubernetes, Helm, and CI/CD
- Experience with AWS Bedrock or SageMaker
- Experience with document or OCR pipelines or PyTorch
- Experience with AI evaluation, hallucination detection, monitoring, or LLMOps
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The Company
What We Do
Emumba is a global software services company specializing in enterprise-grade software, AI systems, cloud, and DevOps solutions, enabling innovation for Fortune 500 customers.
