Forward Deployed Engineer
Insight Global
Key Responsibilities:
15% Stakeholder Engagement & Solution Design
Serve as the technical bridge between business and AI/engineering teams, translating business needs into clear technical and data requirements.
Partner with business stakeholders, product owners, and technology teams to understand workflows and identify where AI can deliver value.
Lead structured technical decomposition to align requirements, constraints, and regulatory considerations with architecture and platform teams.
20% Deployment & Environment Readiness
Assess deployment environments for AI readiness, including infrastructure, access controls, security, and integration dependencies.
Coordinate with cloud, platform, and enterprise architecture teams to ensure environments are production ready.
Identify and mitigate deployment risks early, including scalability, reliability, and compliance considerations.
25% Data Readiness & Process Clarity
Evaluate data availability, quality, lineage, and governance to determine suitability for AI use cases.
Partner with data engineering and business teams to resolve gaps in data sourcing, transformation, and documentation.
Validate that underlying business processes are sufficiently defined, stable, and measurable to support AI driven automation or decisioning.
20% AI Solution Implementation
Support the configuration, integration, and deployment of AI solutions, including models, workflows, and supporting services.
Assist in translating prototypes or proofs of concept into scalable, production grade solutions.
Troubleshoot issues across data pipelines, integrations, and model behavior in live or pre production environments.
10% Adoption, Enablement & Feedback
Enable business and operational teams through documentation, demo, walkthroughs, and knowledge transfer to ensure sustained adoption.
Collect feedback from deployments and surface insights to AI platform, product, and governance teams to improve scalability and reusability.
Help define repeatable deployment patterns and playbooks for future AI implementations across the enterprise.
Required Skills & Experience Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent experience.
Experience in customer facing or deployment oriented technical roles (e.g., solution engineering, implementation, forward deployed roles).
Strong understanding of data driven systems and AI/ML platforms.
Ability to translate ambiguous business needs into clear technical and data requirements.
Familiarity with AI/ML concepts (e.g., MLOps, model lifecycle, LLM based solutions).
Strong communication skills across technical and non technical stakeholders.
Experience deploying AI or advanced analytics solutions in regulated environments (financial services, fintech, healthcare, etc.).
Experience supporting solutions from pilot through production rollout.
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.
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