Forward Deployed Engineer

Job Description 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. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements 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.