Solution Architect – ML Engineering (Pre-Sales, Enterprise AI)
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Job Location:
Ridgefield Park, NJ - USA
Monthly Salary:
Not Disclosed
Posted on:
16 hours ago
Vacancies:
1 Vacancy
Job Summary
Job description
About the Role
Were looking for a hands-on Solution Architect who can bridge technology and business to design scalable AI/ML solutions for our enterprise clients. Youll work closely with sales engineering and data science teams to shape solutions that bring GenAI ML and data engineering to life across industries like tech finance and healthcare.
Key Responsibilities
Partner with sales teams to understand client goals and design end-to-end AI/ML agentic solutions from data pipelines to model deployment and MLOps.
Lead technical discussions and workshops with client teams to shape architecture scope and success metrics.
Build proposals architecture diagrams and PoC plans that showcase Innodatas GenAI and ML capabilities.
Collaborate with delivery and offshore teams to ensure technical feasibility and smooth handoff.
Develop reusable solution playbooks and demo frameworks for repeatable use cases like RAG LLM evaluation and model fine-tuning.
Job requirements
Technical & Required Skills
8 years in ML engineering data science or AI solutioning with 3 years in pre-sales or client-facing roles.
Deep knowledge of LLMs RAG prompt engineering and orchestration tools (LangChain LlamaIndex etc.).
Experience in building end to end Genai copilot or Agents for enterprise such as knowledge bot smart search copilots for application or dashboards agentic workflow automation using MCP/A2A and required tech stack
Experience with cloud AI stacks (GCP Vertex AI AWS SageMaker Azure AI Studio) and MLOps frameworks.
Strong communication and whiteboarding skills able to simplify complex AI concepts for non-technical stakeholders.
A collaborative mindset and curiosity to explore new GenAI use cases.
Preferred Skills and Experience
Experience with enterprise AI implementations or model evaluation/red-teaming.
Cloud or ML certifications (GCP AWS Azure).
Minimum Education Requirements
Bachelors degree or higher in Computer Science Artificial Intelligence Machine Learning Linguistics Localization or a related field.
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Key Skills
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