Specialist Solutions Architect - AI/ML
This role guides customers and field engineers in architecting and productionizing AI/ML workloads, including generative AI, agentic systems, and MLOps. It requires 5+ years of industry ML experience, strong technical communication, and preferably customer-facing pre-sales or post-sales experience.
About the job
Responsibilities
- Architect production-level ML and AI workloads for customers using a unified platform, including agents, end-to-end ML pipelines, training and inference optimization, cloud-native service integrations, and MLOps.
- Serve as a trusted practitioner for enterprise generative AI solutions, including RAG architectures, agentic systems, tool-calling agents, multi-agent orchestration, guardrails, natural-language querying of structured data, AI evaluation and observability, and monitoring systems.
- Build, scale, and optimize customer AI workloads and apply best-in-class MLOps to productionize them across varied domains.
- Provide advanced technical support to Solution Architects during technical sales, covering feature engineering, training, tracking, serving, and model monitoring.
- Participate in the broader ML subject-matter-expert community.
- Collaborate with product and engineering teams to represent customer needs, define priorities, and influence the product roadmap.
Requirements
- 5+ years of hands-on industry machine learning experience in at least one of the following areas:
- Building and maintaining production-grade cloud infrastructure on AWS, Azure, or Google Cloud for deploying ML applications, including drift monitoring.
- Applying current techniques in large language models and agentic systems, including vector databases, LLM fine-tuning, AI guardrails, and deploying LLMs with Hugging Face, LangChain, and OpenAI.
- Graduate degree in a quantitative discipline such as Computer Science, Engineering, Statistics, or Operations Research, or equivalent practical experience.
- Experience communicating or teaching technical concepts to technical and non-technical audiences.
- Ability to collaborate, learn continuously, and drive business value through ML and AI.
- Ability to complete technical training and role-specific outcomes within three months of hire.
- Ability to travel up to 30% when needed.
Nice to Have
- 2+ years of customer-facing experience in a pre-sales or post-sales role.
Compensation and Benefits
- Comprehensive benefits and perks are offered, with region-specific details available through the employer.
Skills
Machine Learning, Generative AI, LLMs, MLOps, RAG, AI Agents, Vector Databases, AWS, Microsoft Azure, GCP, Hugging Face, LangChain, OpenAI, Python, Model Monitoring
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