
Ai Solution Architect
1 week ago
Overview:
**Responsibilities**:
**Presales & Solutioning**
Lead the AI/ML solutioning during presales engagements by assessing client requirements, conducting feasibility analysis, and identifying the right-fit technology stack.
Create solution architectures, conceptual models, and high-level designs aligned to client business goals.
Collaborate with sales teams to drive customer conversations, technical workshops, and demos.
Respond to RFPs/RFIs and develop compelling proposals, effort estimates, and technical presentations.
Translate complex AI concepts into business language for diverse stakeholders, including CXOs.
**Offer Development & Go-to-Market (GTM)**
Develop and package AI solution offerings tailored to industry use cases (e.g., predictive maintenance, customer intelligence, document automation, anomaly detection).
Partner with product and marketing teams to define go-to-market strategies, value propositions, and sales collateral.
Stay updated on emerging trends in AI/ML, GenAI, MLOps, LLMs, and related ecosystems to ensure competitive positioning of offerings.
Support internal capability building by defining solution blueprints, reusable assets, and reference architectures.
**Client Engagement & Delivery Handoff**
Act as a trusted advisor to clients on AI-driven digital transformation initiatives.
Participate in initial project mobilization, ensuring smooth hand-off to delivery teams with a clear understanding of solution architecture, risks, and assumptions.
Support POCs, pilots, and MVPs to validate solution hypotheses and drive stakeholder buy-in.
Qualifications:
Bachelor’s or Master’s in Computer Science, Data Science, Engineering, or related field.
Essential skills:
Deep knowledge of machine learning, deep learning, NLP, LLMs, and MLOps pipelines.
Experience with cloud AI/ML platforms (AWS Sagemaker, Azure ML, Google Vertex AI).
Proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch), and data frameworks.
Demonstrated success in presales roles: proposal writing, effort estimation, pricing strategies.
Excellent communication, presentation, and stakeholder management skills.
Understanding of enterprise architecture, data governance, and compliance (GDPR, HIPAA, etc.).
Desired skills:
Experience with GenAI/LLM use cases and frameworks (LangChain, RAG pipelines, etc.).
Familiarity with business domains like BFSI, Healthcare, Manufacturing, or Retail.
Prior experience working with consulting firms or system integrators is a strong plus.
Certifications in AI/ML (e.g., AWS Certified Machine Learning Specialty, Microsoft AI Engineer) are desirable.
**Experience**:
8+ years of IT experience with at least 3-5 years in designing and architecting AI/ML solutions.
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