Exavalu
Digital Transformation Consulting
See how your profile stacks up against this role.
We compared the job requirements to your profile to show where you're strong and where you fall short.
This is a remote position.
Overview :
Design, build, and deploy production-ready AI applications—including RAG-powered solutions, conversational AI, and document intelligence—on Azure/AWS/GCP. Collaborate with architects, data engineers, and domain SMEs to deliver outcomes in areas like FNOL, claims automation, underwriting, and agent assist.
Key Responsibilities
- Design and implement end-to-end AI/ML solutions from data prep to production deployment.
- Build RAG pipelines with robust retrieval, re-ranking, grounding, and evaluation.
- Develop AI applications such as conversational agents and document intelligence workflows (extraction, classification, validation).
- Implement image/document processing (OCR, layout analysis, table extraction, redaction).
- Integrate with enterprise systems and APIs; enable tool use/function calling where applicable.
- Optimize for latency, accuracy, cost, and safety.
- Package and deploy with Docker/Kubernetes/Serverless; automate with CI/CD.
- Write clean, testable code; contribute to internal accelerators, templates, and best practices.
Required Skills & Experience
- 5+ years of hands-on experience delivering AI/ML software to production.
- Strong in Python and one of PyTorch / TensorFlow.
- Solid understanding of LLMs, prompting, function calling/tools, evaluation, and vector search.
- Experience with RAG (indexing, chunking, embeddings, retrieval, re-rankers, grounding).
- Practical exposure to Document AI and Conversational AI in real-world workflows.
- Cloud experience on Azure, AWS, or GCP.
After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.
Marcus Rivera
Chief Revenue Officer

Insider.

eSimplicity

Mactores

Vanigent

Collaboration.Ai

Exavalu

Exavalu

Exavalu