Presales AI Solutions Architect

About the role

Solvd Inc. seeks a Presales AI Solutions Architect to lead the design and implementation of GenAI and agentic AI solutions for our clients. This role involves shaping innovative AI solutions that align with business needs while ensuring they are secure, scalable, and ready for production.

Responsibilities

• Lead the design of GenAI / Agentic AI-enabled solution architectures and buy vs build decisions that balance innovation, feasibility and scalability.
• Participate in presales by collaborating with sales representatives, deal architects, product analysts, and technology SMEs to define technical scope, implementation roadmap, and effort estimates.
• Translate high-level business use cases into detailed AI system designs covering model strategy, data access, orchestration, and integration patterns.
• Evaluate and select appropriate AI frameworks, platforms, and tools (e.g., LLMs, vector databases, orchestration frameworks, cloud AI services).
• Create architectural artifacts, proof-of-concepts, and technical documentation to support proposals and client discussions.
• Present and defend architectural decisions to both business and technical stakeholders during presales and early project stages.
• Ensure proposed solutions adhere to security, compliance, and Responsible AI principles.
• Stay ahead of industry trends, evaluate new tools and adoption frameworks.

Requirements

• 12+ years of experience in IT, including at least 5 years in solution architecture roles focused on software or cloud systems integration and distributed application design within consulting environments.
• At least 2 years of hands-on experience architecting GenAI or agentic AI systems using modern LLM ecosystems (e.g. OpenAI, Anthropic, Gemini, Azure AI, AWS Bedrock).
• Experience supporting presales solutioning or proposal development for AI engagements.
• Proven ability to translate business or product requirements into scalable AI solution architectures.
• Strong understanding of LLM orchestration, retrieval-augmented generation (RAG), vector databases, and prompt engineering principles.
• Understanding of cost modeling for AI workloads (token usage, inference scaling, hosting models).
• Proficiency with at least one major cloud platform (AWS, Azure (preferred), or GCP) and its AI/ML service offerings.
• Demonstrated experience leading technical discussions with both engineering and non-technical stakeholders in presales or early delivery phases.
• Strong command of software engineering fundamentals, API design, and integration patterns.
• Knowledge of modern software delivery practices (CI/CD, containerization, observability, DevSecOps).
• Excellent communication, presentation, and documentation skills, with the ability to articulate complex solutions clearly and persuasively.

Optional Requirements

• Prior experience with traditional AI/ML systems (model training, MLOps, data pipelines, feature stores).
• Familiarity with frameworks for agentic or multi-component pipelines.
• Exposure to Responsible AI, data privacy, and governance frameworks.
• Experience working with or integrating open-source LLMs or fine-tuning frameworks.
• Hands-on experience with Databricks or Snowflake.
• Industry-recognized cloud and AI certifications (AWS, Azure, GCP).

Benefits

Join a global team with equal opportunities for collaboration across continents and cultures. Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards.

Pay

Competitive salary and benefits package.

Schedule

Full-time position.

Skills

Seasoned solution architect with experience in traditional software or cloud systems integration and distributed application design. Expertise in designing and integrating systems that LLMs and agentic frameworks within modern AI ecosystems. Proficient in combining established engineering patterns with emerging AI capabilities to deliver reliable, production-ready solutions. Skilled in guiding teams through ambiguity, able to prototype rapidly, validate architectural assumptions, and converge toward delivery-ready designs. Comfortable engaging with executives, product teams, and engineers, translating complex AI concepts into clear, actionable solution narratives. Pragmatic, curious, and collaborative, equally focused on technical soundness, business value, and delivery readiness.

Company Culture

Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. Be part of a global team with equal opportunities for collaboration across continents and cultures. Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards.