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Solvd is seeking an AI Solutions Architect to design and lead cutting-edge GenAI and agentic AI solutions for our clients. In this role, you will shape how large language models, orchestration frameworks and enterprise systems come together to deliver measurable business outcomes. You’ll work closely with presales and delivery teams to define architectures that balance innovation with practicality - ensuring our solutions are not only visionary but also secure, scalable and ready for production.
Job Responsibility:
Lead the design of GenAI / Agentic AI-enabled solution architectures and buy vs build decisions that balance innovation, feasibility and scalability
Actively participate in presales partnering 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
At least 5 years in solution architecture roles focused on software or cloud systems integration and distributed application design within consulting environments
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
Nice to have:
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)
What we offer:
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