Presales AI Solutions Architect

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the development of architectures for GenAI / Agentic AI-enabled solutions, making buy vs build decisions that promote innovation, feasibility, and scalability.

• Engage actively in presales alongside sales representatives, deal architects, product analysts, and technology subject matter experts to define the technical scope, implementation roadmap, and effort estimates.

• Convert high-level business use cases into comprehensive AI system designs that encompass model strategy, data accessibility, orchestration, and integration patterns.

• Assess and choose suitable AI frameworks, platforms, and tools (such as LLMs, vector databases, orchestration frameworks, and cloud AI services).

• Develop architectural artifacts, proofs of concept, and technical documentation to bolster proposals and client discussions.

• Present and justify architectural choices to both business and technical stakeholders during presales and the initial stages of projects.

• Ensure that proposed solutions comply with security, compliance, and Responsible AI principles.

• Remain ahead of industry developments, evaluating new tools and adoption frameworks.

⛳️ Requirements

• A minimum of 12 years of experience in IT, with at least 5 years dedicated to solution architecture roles that emphasize software or cloud systems integration and distributed application design within consulting settings.

• Over 2 years of practical experience in architecting GenAI or agentic AI systems utilizing contemporary LLM ecosystems (for example, OpenAI, Anthropic, Gemini, Azure AI, AWS Bedrock).

• Experience in supporting presales solutioning or proposal development for AI initiatives.

• A proven track record of converting business or product requirements into scalable AI solution architectures.

• In-depth knowledge of LLM orchestration, retrieval-augmented generation (RAG), vector databases, and prompt engineering principles.

• Understanding of cost modeling for AI workloads (including token usage, inference scaling, and hosting models).

• Proficient in at least one major cloud platform (AWS, Azure (preferred), or GCP) and its AI/ML service offerings.

• Demonstrated capability to lead technical discussions with both engineering and non-technical stakeholders during presales or early implementation phases.

• Strong grasp of software engineering fundamentals, API design, and integration patterns.

• Familiarity with modern software delivery practices (CI/CD, containerization, observability, DevSecOps).

• Excellent communication, presentation, and documentation skills, with the ability to convey complex solutions in a clear and persuasive manner.

• Previous experience with traditional AI/ML systems (model training, MLOps, data pipelines, feature stores).

• Knowledge of frameworks for agentic or multi-component pipelines.

• Exposure to Responsible AI, data privacy, and governance frameworks.

• Experience with or integrating open-source LLMs or fine-tuning frameworks.

• Hands-on experience with Databricks or Snowflake.

• Possession of industry-recognized cloud and AI certifications (AWS, Azure, GCP).

🏝️ Benefits

• Influence real-world AI-driven projects across various key industries, collaborating with clients from startup innovation to enterprise transformation.

• Join a global team that offers equal opportunities for collaboration across continents and cultures.

• Flourish in an inclusive environment that emphasizes continuous learning, innovation, and ethical AI standards.