Specialist Solution Architect, AI - Ecosystem

Accountabilities

• Deliver technical presentations, demonstrations, workshops, and solution deep dives to partners and stakeholders, showcasing AI capabilities and business value.


• Support pre-sales activities by contributing to technical proposals, architecture designs, RFIs, RFPs, and other solution-related documentation.


• Collaborate with partner solution architects, account teams, and technical stakeholders to identify challenges, remove adoption barriers, and accelerate AI initiatives.


• Design, architect, and guide the implementation of AI solutions, including machine learning pipelines, data architectures, model training environments, and deployment frameworks.


• Support proof-of-concept projects, technical evaluations, hackathons, workshops, and innovation initiatives that demonstrate solution value and feasibility.


• Drive ecosystem adoption by enabling partners to develop industry-specific AI use cases and scalable customer solutions.


• Act as a trusted technical advisor, helping align AI strategies, business goals, and technology roadmaps across stakeholder groups.


• Collaborate closely with product management, engineering, and technical teams to provide market feedback and contribute to product evolution.


• Create reusable technical assets, best-practice documentation, templates, and enablement materials that support scalable partner success.


• Mentor less-experienced team members and contribute to knowledge sharing across the broader technical community.


• Participate in industry events, conferences, community initiatives, public speaking engagements, and thought leadership activities.

Requirements

• Hands-on experience in artificial intelligence, machine learning, data science, MLOps, LLMOps, or related technical domains.


• Practical experience developing AI applications, including areas such as large language models (LLMs), retrieval-augmented generation (RAG), natural language processing, deep learning, computer vision, or predictive analytics.


• Strong proficiency in Python or other statistical programming languages used for machine learning and AI development.


• Experience working with leading open-source AI and machine learning frameworks such as TensorFlow, PyTorch, or similar technologies.


• Knowledge of AI system architecture, data pipelines, machine learning pipelines, model training, deployment, monitoring, and operationalization.


• Familiarity with DevOps, CI/CD practices, Infrastructure as Code (IaC), automation tools, and cloud-native environments.


• Strong communication and presentation skills with the ability to explain complex technical concepts to both technical and business audiences.


• Experience leading workshops, technical demonstrations, architecture reviews, or customer-facing technical discussions.


• Ability to quickly learn new technologies and adapt to evolving AI trends and industry requirements.


• Strong collaboration, stakeholder management, and problem-solving skills.


• Comfortable working in a remote and highly collaborative international environment.

Preferred Qualifications:

• Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.


• Previous experience in technical pre-sales, sales engineering, solution architecture, consulting, or implementation roles within enterprise software, SaaS, or systems integration environments.


• Experience implementing AI solutions for enterprise customers.


• Knowledge of MLOps, LLMOps, AI governance, and scalable production AI systems.


• Industry expertise in sectors such as financial services, healthcare, defense, intelligence, or other data-intensive industries.


• Active involvement in open-source communities, AI user groups, technical forums, or community-driven technology initiatives.


• Experience contributing technical content through presentations, blogs, publications, or community events.

Benefits

• Competitive compensation package.


• Flexible and remote-first working environment.


• Opportunities for continuous learning, certification, and professional development.


• Access to cutting-edge AI technologies, tools, and industry-leading technical communities.


• Collaborative and inclusive workplace culture.


• Exposure to global projects, international teams, and diverse industry challenges.


• Career growth opportunities within a highly innovative technology environment.


• Flexible work arrangements designed to support work-life balance.


• Mentorship and knowledge-sharing opportunities with experienced AI specialists and engineering teams.


• Participation in conferences, workshops, and community engagement initiatives.

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