Innodata Inc
Solution Architect – ML Engineering (Pre-Sales, Enterprise AI)
Innodata Inc, Ridgefield Park, New Jersey, us, 07660
About the Role
We’re looking for a hands‑on Solution Architect who can bridge technology and business to design scalable AI/ML solutions for our enterprise clients. You’ll 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 Innodata’s 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.
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 copilots or agents for enterprise such as knowledge bots, smart search, copilots for applications 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
Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Linguistics, Localization, or a related field.
Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams.
If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.
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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 Innodata’s 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.
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 copilots or agents for enterprise such as knowledge bots, smart search, copilots for applications 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
Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Linguistics, Localization, or a related field.
Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams.
If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.
#LI-NS1
#J-18808-Ljbffr