Apgar is a leading international consulting firm specializing in data strategy, data platforms, and data management. Recognized by top industry analysts, we support major global companies in turning their critical data into a strategic asset. At Apgar, our DNA is built on four core values: Commitment, Excellence, Partnership, and Ethics. We believe in a human-centric approach, offering an environment where flexibility, continuous coaching, and cross-functional mobility allow every "Apgarian" to reveal their full potential.
Role Overview
The AI Solution Architect plays a strategic and technical leadership role in shaping, promoting, and delivering innovative AI solutions. Leveraging expertise in Agentic AI, Machine Learning, Natural Language Processing (NLP), Information Retrieval, and Software Development, the AI Solution Architect designs scalable architectures, supports business development efforts, drives presales activities, and leads AI solution adoption across client organizations.
The role combines technical leadership, solution design, client engagement, team coordination, and innovation to ensure the successful growth and delivery of Apgar's AI offerings.
Your Mission
As an AI Solution Architect, you will lead the design and promotion of intelligent solutions that address complex business challenges through Artificial Intelligence and Generative AI technologies.
You will work closely with clients, business stakeholders, and consulting teams to define AI strategies, design robust architectures, oversee implementation approaches, and accelerate the adoption of AI-powered solutions. You will also contribute to expanding Apgar's AI footprint by supporting presales activities, developing client relationships, and promoting AI solutions across industries.
Key Responsibilities
AI Strategy & Solution Architecture
- Design end-to-end AI solution architectures aligned with client business objectives.
- Define technical roadmaps for AI initiatives, from ideation through deployment and scaling.
- Architect solutions leveraging Agentic AI, Generative AI, Machine Learning, NLP, Information Retrieval, and enterprise software technologies.
- Ensure solution scalability, security, performance, maintainability, and governance.
- Define integration patterns between AI solutions and enterprise systems.
- Drive adoption of best practices in AI architecture, MLOps, LLMOps, and Responsible AI.
Client Engagement & Business Consulting
- Act as a trusted advisor to clients throughout their AI transformation journey.
- Collaborate with business leaders to identify opportunities where AI can create measurable value.
- Translate business challenges into innovative AI-driven solutions.
- Conduct discovery workshops, assessment sessions, and strategic advisory engagements.
- Present technical and business recommendations to executive stakeholders.
- Support clients in defining AI adoption roadmaps and governance frameworks.
Presales & Solution Positioning
- Lead technical presales activities for AI opportunities.
- Participate in client presentations, workshops, demonstrations, and proof-of-concept discussions.
- Design solution proposals and technical approaches in response to RFPs and client requirements.
- Support effort estimation, project scoping, and resource planning.
- Develop compelling value propositions demonstrating the business impact of AI initiatives.
- Contribute to proposal writing and solution documentation.
AI offering Development & Promotion
- Serve as a key ambassador for Apgar's AI offerings.
- Demonstrate AI use cases, accelerators, and industry-specific solutions to prospects and clients.
- Collaborate with marketing and business teams to promote AI thought leadership.
- Contribute to webinars, conferences, workshops, and client showcases.
- Develop reusable solution frameworks, accelerators, and AI assets.
Technical Leadership & Team Coordination
- Provide technical leadership to AI consultants and project teams.
- Guide architecture decisions throughout project lifecycles.
- Mentor junior and senior AI consultants on best practices and emerging technologies.
- Facilitate knowledge sharing and innovation within the AI team.
- Coordinate technical activities across AI engagements and initiatives.
- Review solution designs and ensure alignment with architectural standards.
Innovation & Research
- Continuously evaluate emerging AI technologies, frameworks, and market trends.
- Explore advancements in Agentic AI, LLM ecosystems, Retrieval Augmented Generation (RAG), multi-agent systems, and enterprise AI architectures.
- Lead experimentation initiatives and proof-of-concepts.
- Recommend new technologies and approaches that strengthen Apgar's AI capabilities.
- Contribute to the evolution of AI methodologies and delivery frameworks.
Your Profile
Education
- PhD, Master’s degree, or Engineering Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Computational Linguistics, Mathematics, or a related field.
Experience
- 7+ years of experience in Artificial Intelligence, Software Engineering, Data Science, or related domains.
- Demonstrated experience designing enterprise-scale AI solutions.
- Experience leading client-facing AI initiatives and consulting engagements.
- Proven involvement in presales, solution architecture, and business development activities.
Technical Expertise
Artificial Intelligence
- Expertise in Agentic AI architectures and AI orchestration frameworks.
- Strong experience with Machine Learning and Generative AI solutions.
- Extensive knowledge of Natural Language Processing (NLP) and conversational AI systems.
- Experience in Information Retrieval, Knowledge Management, and RAG architectures.
- Understanding of LLM evaluation, optimization, and governance frameworks.
Software Engineering
- Strong software architecture and design capabilities.
- Proficiency in Python and modern development frameworks.
- Experience building enterprise-grade AI applications and APIs.
- Knowledge of microservices, cloud-native architectures, and distributed systems.
Cloud & Infrastructure
- Familiarity with Azure, AWS, or Google Cloud AI services.
- Experience with containerization and orchestration technologies.
- Understanding of MLOps, LLMOps, deployment automation, and monitoring practices.
Business & Leadership Skills
- Strong stakeholder management and relationship-building capabilities.
- Excellent presentation, communication, and facilitation skills.
- Ability to explain complex AI concepts to both technical and non-technical audiences.
- Strong analytical thinking and problem-solving abilities.
- Proven ability to influence strategic decisions and drive innovation.
- Entrepreneurial mindset with a strong focus on value creation and business impact.
