Responsibilities and Duties:
As an AI Solution Strategist, you will play a pivotal role in identifying, shaping, and securing new AI opportunities by bridging the gap between complex customer challenges and transformative, AI-powered solutions. This highly consultative role requires a strong blend of technical expertise, business acumen, and communication skills. You will work closely with clients, account teams, and delivery leads to understand customer needs, design compelling AI solutions, and contribute to successful bid strategies and proposals.
You are expected to act as a trusted advisor to both internal teams and client stakeholders, translating real-world challenges into scalable AI architectures that demonstrate tangible business value. Your work will directly support sales growth by influencing solution design, estimating effort and risk, and differentiating our offer through innovation and credibility.
Shape AI Solutions in Response to Client Needs
Engage with client stakeholders to uncover pain points, business drivers, and opportunities for AI-powered transformation. Conduct discovery workshops and assessments to define business requirements and align them with AI use cases.
Design and Propose AI Architectures
Translate client requirements into scalable, cloud-based AI architectures that address both technical feasibility and business impact. Propose end-to-end AI/ML solutions—including model design, data pipelines, MLOps, and platform integration—tailored to each opportunity.
Support Sales and Bid Activity
Lead the technical response for AI-related RFPs, RFIs, and proposals, including solution overviews, technical narratives, architecture diagrams, and estimates. Contribute to bid strategy, win themes, and differentiators based on the latest AI technologies (e.g. GenAI, LLMs, computer vision, NLP, predictive modelling).
Prototype and Demonstrate
Build proof-of-concepts (PoCs) or demos to validate solution approaches and inspire client confidence. Showcase AI capabilities using Calix’s tools.
Track Industry Trends and Use Cases
Stay ahead of market trends in Generative AI, Responsible AI, and emerging AI use cases across sectors. Advise internal stakeholders on how evolving technologies (e.g. vector databases, RAG pipelines, prompt engineering) can drive value in future proposals.
Qualifications:
Proven experience in pre-sales or client-facing architecture roles involving AI, data science, or analytics.
Strong ability to elicit business needs and align them with AI/ML solutions in cloud environments like GCP.
Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search.
Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face.
Ability to develop architecture artefacts (e.g., HLDs), estimate effort and cost, and contribute to proposal writing.
Strong storytelling and presentation skills; able to build confidence with senior business and technical stakeholders.
Experience working in bid teams or alongside account executives, ideally in a consultancy or solution provider context.
Understanding of data governance, security, and ethical AI practices.
Ability to adapt solutions across multiple business departments.
Ability to work as part of a team to solve technical problems in varied political environments.
Must have a valid driver's license and passport.
Travel is required.
Core Competencies:
Strong collaboration
Clear communication
Instills trust
Natural storytelling ability
Organization
Accountability
Desired Experiences:
Experience in software/SaaS solutions are required.
Comprehensive understanding of how to identify customer value and align the sales cycle to the customer’s business and technical objectives.
Ability to negotiate an executive level commercial/procurement cycle.
Proven track record and experience in solving IT challenges in an enterprise environment either as a technologist in IT or as a consultant to IT.
Previous sales methodology training (Value Selling, Challenger, SPIN).
Education:
Bachelor or University Degree Strongly Preferred
The on-target earnings for this position varies based on the geographic location. More information about the pay range specific to candidate location and other factors will be shared during the recruitment process. Individual pay is determined based on location of residence and multiple factors, including job-related knowledge, skills and experience.
San Francisco Bay Area:
311,000 - 467,000 USD AnnualSelect US Metros and States:
270,000 - 405,000 USD AnnualOther US Locations:
243,000 - 365,000 USD AnnualFor information on our benefits click here.
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