Wisdom Tree
Website:
wisdom-tree.net
Job details:
WisdomTree LLP is building an end-to-end AI & Data ecosystem for enterprise clients, moving organizations from vision to scalable reality through the Discover → Develop → Deploy framework. We’re looking for a hands-on Computer Engineer to join the Deploy pillar, working alongside senior Fractional CTOs to research, map, and prototype opportunities in Global Capability Centers (GCCs) and Agentic AI. This is a research-meets-build role: you’ll study how GCCs are structuring their AI investments, identify solution and pilot opportunities in agentic AI, and get hands-on experience building proof-of-concepts that feed into board-ready client roadmaps.
Responsibilities
- GCC Landscape Mapping: Research and track how Global Capability Centers (in India and other hubs) are adopting AI — their org structures, tech stacks, maturity levels, and investment patterns.
- Opportunity Identification: Surface specific agentic AI use cases and solution gaps within GCCs that align with client KPIs and business priorities.
- Pilot Support: Assist Fractional CTOs in scoping and building 2–4 week proof-of concept pilots for agentic AI solutions (e.g., AI data concierge tools, prediction/forecasting engines, campaign automation agents).
- Technical Diagnostics: Support hands-on assessments of client data infrastructure, workflows, and AI-readiness using the MIT 3-Lens Framework (Strategy, Infrastructure, Culture).
- Documentation & Roadmapping: Help translate research and pilot findings into structured, board-ready deliverables (roadmaps, business cases, use-case portfolios).
- Cross-Functional Collaboration: Work closely with Fractional CTOs, data engineers, and AI specialists embedded in client teams — not offshore or siloed delivery.
What You’ll Gain
- Direct exposure to enterprise AI deployment strategy under senior Fractional CTOs.
- Hands-on experience building and testing agentic AI pilots.
- Insight into how GCCs are evolving as AI innovation hubs Mentorship from a team of MIT, Harvard, and industry veterans.
- A foundation in enterprise consulting, technical diagnostics, and AI investment casebuilding.
Required Qualifications:
- Final-year student in Computer Engineering, Computer Science, or a closely related field.
- Working knowledge of Python and API-based development Familiarity with data infrastructure concepts (pipelines, governance, cloud platforms) Strong research and synthesis skills — comfortable digging into market/industry landscapes.
- Ability to communicate technical findings clearly to non-technical stakeholders
Preferred Qualifications:
- Hands-on experience with at least one AI/ML framework or agentic AI tooling (e.g., LangChain, AutoGen, CrewAI, or similar).
- Prior exposure to or coursework in enterprise AI, NLP, or LLM-based systems.
- Experience with a personal or academic project involving agent-based or autonomous AI systems.
- Understanding of the GCC (Global Capability Center) model and enterprise IT landscape.
- Prior internship or project experience in a consulting, strategy, or client-facing technical role.
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