Solutions Architect 3

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Solutions Architect 3 based in United States.

As a Solutions Architect 3, you will lead the architecture of complex AI-driven solutions from concept through production.
You will translate ambiguous business needs into scalable, secure, and resilient technical architectures.
The role combines deep expertise in Generative AI and RAG with modern cloud-native and distributed systems architecture.
You will work closely with business leaders, product owners, engineering teams, and other architects across the US.
Your guidance will shape enterprise AI standards, technology choices, and long-term platform strategies.
The position offers a high level of technical ownership, with opportunities to evaluate emerging technologies and bring them into production.
Candidates with telematics or automotive industry experience are particularly well suited to the environment.

Accountabilities:

• Own and define end-to-end solution and platform architectures for large-scale, distributed systems from concept through production.
• Design architectures that meet demanding standards for scalability, performance, resilience, security, and cost efficiency.
• Translate business and non-functional requirements into durable technical solutions aligned with business outcomes.
• Partner with business leaders, product owners, engineering managers, and delivery teams to maintain architectural alignment.
• Define AI reference architectures and enterprise standards, including solutions involving Generative AI, RAG, and agentic frameworks.
• Evaluate, prototype, and introduce emerging technologies through proofs of concept and architectural spikes.
• Establish and enforce architecture standards, patterns, and best practices across platform and engineering teams.
• Provide technical guidance and mentorship to engineering teams throughout implementation.
• Ensure solutions comply with security, privacy, regulatory, and enterprise requirements.
• Create and maintain clear architecture documentation covering design decisions, tradeoffs, standards, and rationale.
• Continuously evolve platform architectures to improve developer productivity, reliability, scalability, and cost efficiency.
• Architect end-to-end AI workflows covering prompt design, context management, model routing, retrieval, evaluation, monitoring, and lifecycle management.
• Design RAG pipelines covering data ingestion, document preprocessing, chunking, embeddings, retrieval, ranking, and context assembly.
• Integrate AI capabilities into existing enterprise platforms through APIs and event-driven architectures.
• Assess architectural tradeoffs between classical machine learning, LLM-based approaches, and non-AI solutions based on business requirements.

Requirements:

• Bachelor’s degree with 5+ years of experience in an architecture role, including at least 5–6 years of hands-on AI architecture experience.
• Proven experience designing, owning, and scaling AI solutions at the architecture level, with strong expertise in Generative AI and RAG.
• Strong architectural thinking, with the ability to decompose complex problems and develop pragmatic options with clearly articulated tradeoffs.
• Demonstrated ability to influence technical decisions without direct authority and guide teams through complex implementation challenges.
• Excellent communication skills, with the ability to explain sophisticated technical concepts to both technical and non-technical stakeholders.
• Strong foundation in modern application and platform architecture, including enterprise-scale distributed systems.
• Proven experience taking AI solutions from proof of concept through production and scaled enterprise adoption.
• Hands-on experience with RAG architectures, including vectorization, embedding models, similarity search, retrieval strategies, and context assembly.
• Understanding of vector databases and search layers, including tradeoffs involving vector dimensions, chunking, latency, recall, and cost.
• Experience with agentic AI frameworks and end-to-end AI workflow architecture.
• Strong understanding of LLM lifecycle considerations, including model selection, hosted versus self-hosted models, fine-tuning, RAG, hybrid approaches, evaluation, monitoring, and drift detection.
• Knowledge of AI system non-functional requirements, including latency optimization, token efficiency, cost controls, security, data privacy, and guardrails.
• Strong programming background in Python and Java, with the ability to reason at code level.
• Hands-on experience with cloud-native architectures, including AWS, Docker, and Kubernetes.
• Deep understanding of data architecture, including SQL and NoSQL databases, data warehouses such as Snowflake, data modeling, replication, and sharding.
• Experience with modern DevOps practices, including CI/CD, infrastructure as code, observability, and automated testing.
• Strong API design experience with REST, GraphQL, or gRPC, including versioning and documentation.
• Experience integrating AI capabilities into enterprise platforms through APIs and event-driven architectures.
• Ability to evaluate, prototype, and productionize emerging technologies in alignment with business use cases.
• Experience in the telematics or automotive industry is strongly preferred.
• Candidates should ideally be based in the Chicago or Peoria, Illinois area; remote US candidates should be open to relocation or travel as required.
• MLOps experience is a plus.

Benefits:

• 100% remote opportunity for candidates residing in the United States.
• Preferred location in the Chicago or Peoria, Illinois area.
• 12-month contract opportunity.
• Opportunity to work on complex enterprise AI architecture initiatives.
• High-impact role with significant technical ownership and influence over architecture strategy.
• Collaboration with business leaders, product owners, engineering teams, and architecture professionals across the US.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.