AI Architect / Technical Lead

About Exavalu

Founded in 2018 and headquartered in Newport Beach, California, Exavalu is built by former CIOs, CXOs, and Big 5 consulting leaders. We specialize in delivering enterprise-scale digital transformation solutions across Insurance, Banking & Financial Services, and Healthcare industries.

With delivery centers across India, Canada and the US, Exavalu is recognized for its agile culture, innovation mindset, and employee-first environment. We are committed to building modern, scalable, and business-driven technology solutions for global enterprise clients.

Why Exavalu

• Opportunity to work with global enterprise customers

• Exposure to modern technology stacks and enterprise transformation projects

• Strong learning, growth, and innovation-driven culture

• Collaborative engineering environment with high-impact project exposure

Position: AI Architect / Technical Lead

Experience: 10+ years

Location: Remote

Employment Type: Full-Time

About the Role

We are looking for an AI Architect/Technical Lead who can design and build production-grade AI and Generative AI solutions and lead the engineering journey from experimentation to enterprise-scale deployment.

The ideal candidate should be a hands-on AI/ML engineering leader with strong expertise in Generative AI, LLMs, RAG, AI orchestration and AWS AI services, with the ability to architect scalable, secure and responsible AI solutions.

You Will Get the Opportunity to Work On

• Cutting-edge AI & Generative AI solutions
• Modern Cloud technologies and the AWS ecosystem
• LLMs, RAG and enterprise AI platforms
• Large-scale Data & AI engineering challenges
• Enterprise and regulated-industry use cases
• Building AI solutions that move beyond experimentation into real production environments
• Designing scalable and responsible AI architectures for enterprise clients

If you enjoy solving complex problems and want to be part of building intelligent, scalable and responsible AI solutions, we'd love to hear from you!

Key Responsibilities

• Architect, design and develop production-grade AI/ML and Generative AI solutions.
• Lead the engineering of LLM-based applications, RAG pipelines and enterprise AI platforms.
• Design and implement AI orchestration frameworks for multi-step AI workflows and enterprise use cases.
• Build scalable Data & AI pipelines across cloud and enterprise environments.
• Leverage AWS services such as Amazon Bedrock and Amazon SageMaker to develop and deploy AI solutions.
• Design cloud-native architectures using AWS Lambda, S3, Glue and EKS.
• Establish and implement MLOps practices, including CI/CD, model versioning, monitoring and automated deployment.
• Work with Vector Databases and retrieval architectures for enterprise RAG applications.
• Ensure AI systems are designed with appropriate security, governance, guardrails and Responsible AI principles.
• Collaborate with Data Engineering, Cloud, Product and Business teams to translate complex business requirements into scalable AI solutions.
• Provide technical leadership and mentorship to AI/ML engineers.
• Evaluate emerging AI technologies and identify opportunities to bring them into production.

What We're Looking For

Technical Expertise

• 10+ years of overall technology experience, with at least 3–5+ years of hands-on AI/ML engineering experience.
• Strong hands-on experience building production-grade AI/ML systems.
• Strong expertise in:
• Generative AI
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• NLP
• AI/ML engineering
• AI orchestration experience is mandatory.
• Strong hands-on experience with AWS Bedrock and Amazon SageMaker.
• Good knowledge of:
• AWS Lambda
• Amazon S3
• AWS Glue
• Amazon EKS
• Experience building and deploying Data & AI pipelines.
• Strong understanding of MLOps, CI/CD, monitoring and model versioning.
• Experience with Vector Databases such as Pinecone, Weaviate or equivalent technologies.
• Exposure to Docker and Kubernetes.
• Strong understanding of AI security, Responsible AI, guardrails and AI governance.
• Ability to translate AI concepts and prototypes into scalable, production-ready enterprise solutions.

Preferred / Good to Have

• Experience working with Insurance or other regulated industries.
• Experience designing enterprise-grade AI platforms.
• Experience working with complex enterprise data environments.
• Exposure to multi-agent AI systems and agentic workflows.
• Experience leading or mentoring AI/ML engineering teams.
• Strong understanding of cloud architecture and distributed systems.