Key Facts

Remote From:

Alabama (USA)

Full time

Mid-level (2-5 years)

English

Hard Skills

Other Skills

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Collaboration
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Adaptability
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Communication
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Teamwork
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Problem Solving

Roles & Responsibilities

2–5 years of hands-on experience delivering AI/ML software to production
Strong in Python and PyTorch or TensorFlow
Solid understanding of LLMs, prompting, function calling/tools, evaluation, and vector search
Experience with RAG (indexing, chunking, embeddings, retrieval, re-rankers, grounding) and cloud experience on Azure/AWS/GCP

Requirements:

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 conversational AI and document intelligence workflows
Implement image/document processing (OCR, layout analysis, table extraction, redaction) and integrate with enterprise systems and APIs; enable tool use/function calling where applicable
Package and deploy with Docker/Kubernetes/Serverless; automate with CI/CD; write clean, testable code; contribute to accelerators, templates, and best practices

Job description

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.

Requirements

Required Skills & Experience

- 2–5 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.

- Experience in insurance (FNOL, claims adjudication, underwriting, billing, policy servicing, agent portals, etc.) will be preferred

Benefits

Diversity Inclusion: At Exavalu, we are committed to building a diverse and inclusive workforce. We welcome applications for employment from all qualified candidates, regardless of race, color, gender, national or ethnic origin, age, disability, religion, sexual orientation, gender identity or any other status protected by applicable law. We nurture a culture that embraces all individuals and promotes diverse perspectives, where you can make an impact and grow your career. Exavalu also promotes flexibility depending on the needs of employees, customers and the business. It might be part-time work, working outside normal 9-5 business hours or working remotely. We also have a welcome back program to help people get back to the mainstream after a long break due to health or family reasons.

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