Senior AI Engineer - LLM and AI Systems
Senior AI Engineer / AI Solutions Architect
AI SaaS Products · LLM Systems · Cloud AI (AWS)
Location: Remote / Hybrid (US Preferred)
Employment Type: Full-Time | Senior Level
About the Role
We are seeking an experienced Senior AI Engineer / AI Solutions Architect to design and deliver next-generation AI-powered SaaS products. This role sits at the intersection of large language models, cloud architecture, and enterprise workflow systems.
You will lead the technical design and deployment of scalable AI solutions that solve real-world enterprise problems across procurement, operations, and intelligent automation.
This is a high-impact role for someone who enjoys building production-grade AI systems — not prototypes — and shaping AI strategy alongside product and leadership teams.
What You’ll Do
AI Product Engineering
- Architect and develop AI-driven SaaS capabilities from concept to production.
- Design scalable AI pipelines using:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Agentic workflows and tool-using systems
- Translate business requirements into robust AI system architectures.
- Own end-to-end AI feature delivery:
- Prompt engineering
- Model evaluation
- Performance optimization
- Deployment and monitoring.
LLM & Applied AI Development
- Build enterprise applications powered by modern foundation models.
- Design advanced prompting strategies and multi-turn conversational systems.
- Develop agent-based workflows integrating APIs, tools, and enterprise data.
- Establish best practices for responsible, secure, and scalable AI usage.
- Evaluate emerging models and integrate improvements into production systems.
Cloud & AI Infrastructure
- Design and operate cloud-native AI systems on AWS, including:
- SageMaker
- Bedrock
- Lambda
- ECS/EKS
- API Gateway
- Build scalable inference and data pipelines.
- Partner with DevOps/MLOps teams on:
- CI/CD automation
- Monitoring & observability
- Model lifecycle management.
- Support SaaS deployment and marketplace integrations.
Technical Leadership
- Serve as a technical leader and mentor to AI and engineering teams.
- Collaborate with product, sales, and customer teams to define AI solutions.
- Participate in enterprise customer discussions and solution design.
- Contribute to architectural standards, documentation, and best practices.
Required Qualifications
- 7+ years in software engineering, AI/ML engineering, or solutions architecture.
- Proven experience shipping production AI or LLM-powered applications.
- Strong Python expertise.
- Experience with AI frameworks such as:
- LangChain
- LlamaIndex
- Hugging Face (or similar ecosystems).
- Strong understanding of cloud-native architectures (AWS preferred).
- Experience designing APIs and microservices.
- Ability to communicate complex technical ideas clearly to both technical and business stakeholders.
- Comfortable working in fast-paced startup environments.
Preferred Qualifications
- Hands-on experience building applications with modern LLM APIs.
- Experience with:
- RAG architectures
- Vector databases (Pinecone, Weaviate, pgvector)
- Agent frameworks and orchestration systems.
- Familiarity with AI evaluation frameworks and model benchmarking.
- Experience supporting enterprise deployments or pre-sales engineering.
- AWS certifications (Solutions Architect or ML Specialty).
- Exposure to SaaS marketplace ecosystems or cloud go-to-market models.
- Contributions to open-source AI projects or technical publications.
What Success Looks Like
- Production-ready AI features shipped rapidly and reliably.
- Scalable AI architecture supporting enterprise customers.
- Measurable business outcomes driven by AI automation.
- Strong engineering standards and reusable AI frameworks.
What We Offer
- Competitive salary
- Opportunity to shape core AI architecture and product direction.
- Access to cutting-edge AI models and infrastructure.
- Remote-first, collaborative engineering culture.
- Learning and professional development support.
• High ownership, low bureaucracy environment.