Forward Deployed AI Strategist

For more than 80 years, our client’s engineers and product specialists have partnered with customers to produce highly engineered connectivity and sensing solutions that make a connected world possible. Their focus on reliability, durability, and sustainability exemplifies their commitment to progress. The unmatched range of their product portfolio enables companies, large and small, to turn ideas into technology that can transform how the world works and lives tomorrow.

Role Description:

• The Strategy team is looking for a hands-on AI-enabled strategy and market intelligence professional to materially accelerate the way we conduct deep research, market intelligence, analytical modeling, and GTM analysis by applying high impact AI workflows and translating them into sharper strategic decisions.
• The individual will partner with business, product, commercial, and tech teams to translate ambiguous questions into actionable insights, while developing and scaling AI-enabled solutions that improve strategic decision-making and drive measurable business impact. 
• The individual is expected to work in close partnership with our client IT team, to leverage existing AI & data capabilities on Databricks & AWS (where applicable) while developing solutions.

Responsibilities:

Strategic problem solving and driving cross-functional execution 

• Translate AI-assisted analyses into practical executive decisions by applying strong business judgment, rigorous validation protocols, and a sharp “so-what” orientation
• Collaborate with and influence senior stakeholders across strategy, sales, technology teams, and P&L owners
• Good first-principles and problem-solving capabilities with the ability to build and test strategic hypotheses Identifying meaningful opportunities to leverage AI and deploying scaled AI solutions at pace

Identify, assess, and prioritize high-value AI and automation opportunities by translating business challenges into scalable, practical solutions 

• Design proprietary AI-enabled workflows, agents, and accelerators for recurring strategy activities (competitor monitoring, earnings call tracking, tariff and regulatory intelligence, voice-of-customer mining etc.)
• Build reusable templates, workflows, and modules to drive adoption and embed AI capabilities into strategy processes

Executing rapid AI-augmented research and competitive intelligence 

• Lead AI-augmented research using tools like Claude, OpenAI, Perplexity, AlphaSense, CapIQ etc. to deliver source-triangulated competitive and industry insights
• Synthesize structured datasets (S&P Capital IQ, Bloomberg, IDC, Gartner) and unstructured sources (10-Ks, analyst reports, expert interviews) – to generate and validate AI-assisted outputs

Support strategy team in day-to-day execution by leveraging AI-led tools

• Lead AI-enabled market sizing, opportunity mapping, and TAM/SAM/PAM modelling
• Accelerate financial modelling – scenario and sensitivity analyses, valuation, NPV/IRR, segment P&Ls, pricing
• Support M&A pipeline by AI-screening targets and generating investment theses

AI enablement, coaching and continuous innovation

• Coach strategy team members on prompting techniques, research workflows, and AI-fluent execution
• Scale AI adoption across Corporate Strategy through hands-on mentorship of beginner users
• Stay current on agentic stacks, multimodal models, and deep research agents

Requirements:

Skillset and capabilities

AI fluency and hands-on deployment orientation 

• Working knowledge of GenAI patterns – LLM capabilities/limitations, prompt design, etc.
• Proven ability to convert business problems into reusable AI workflows, tools, or accelerators
• Builder mindset with experience prototyping AI solutions using frontier tools & low-code platforms

Analytics, modelling, and research excellence

• Strong modelling skills across TAM/SAM/PAM, scenarios, sensitivities, NPV/IRR, valuation etc.
• Ability to synthesize structured datasets with unstructured sources
• Research discipline – source triangulation and rigorous validation of AI outputs

Strategic problem solving, communication, executive presence, and influence 

• Sharp "so-what" orientation to translate AI outputs into practical executive decisions
• Crisp written and verbal communication, with ability to frame board-ready narratives
• Skill in explaining AI workflows and implications to both technical and non-technical audiences
• Stakeholder management across strategy, commercial, data, and technology teams

Ownership, and execution

• Independently own workstreams end-to-end – from framing through deployment
• High bar for quality; never publishes unchecked AI outputs or unvalidated analysis

Coaching and capability building 

• Patience and ability to coach colleagues on prompting, research workflows, and source validation
• Track record of building reusable playbooks – templates and training modules that scale adoption

Passion, curiosity, and learning agility

• Deep passion for AI, tech, and industrial innovation, with curiosity to stay current on frontier tools
• Entrepreneurial ownership mindset and drive to build a new AI-enabled strategy capability

Qualifications: 

• BE / B-Tech in Computer Science Engineering, Data Science or a related analytical field required; MBA, MS, M-Tech or equivalent advanced degree strongly preferred.
• 3–4+ years of experience in AI transformation, analytics, or AI-enabled business building. Prior Forward Deployed Engineer / Solutions Architect / Senior Data Scientist background preferred.
• Experience in a top-tier strategy consulting firm, AI-native consulting team, analytics firm or corporate / product strategy team role strongly preferred.
• Demonstrated experience building or deploying 0–1 AI solutions (not just experimenting), GenAI, analytics, automation, or workflow solutions in a business environment required.
• Proficiency in Excel and PowerPoint required; Python or equivalent scripting capability strongly preferred. Experience with DevOps, CI/CD pipelines, and infra as code (e.g., Jenkins, Docker, Kubernetes) required.
• Proficient in implementing AI platforms like AWS Bedrock, LangGraph, Crew AI, Glean etc.
• Knowledge of enterprise data environments (esp. SAP, Databricks) or cloud platforms (esp. AWS) is a plus. Experience integrating AI systems with enterprise data platforms required.
• Experience with LLM-powered solutions, RAG systems, agentic workflows, AI research tools, or AI-enabled knowledge manage