Solutions Architect

We are looking for a senior Solutions Architect to be the chief technical authority for our most strategic and complex customer deployments. You are the evangelist and the architect who designs the end-to-end blueprint for the customer's "AI Workforce."

‍

This is a deeply technical, hands-on role. You will be responsible for designing and guiding the implementation of production-level AI solutions, including complex RAG architectures, multi-agent systems, and the underlying MLOps pipelines. You will serve as the trusted technical advisor to our customers' C-level executives and their engineering teams, ensuring the solutions we build are scalable, secure, and performant.

• Architect Production AI Solutions: Design and architect scalable, production-level AI solutions for customers using our platform. This includes designing RAG architectures, multi-agent systems, and end-to-end MLOps pipelines.
• Act as the Trusted Technical Advisor: Serve as the senior-most technical expert for strategic customers and internal teams. You will provide best practices on AI agent implementation, data governance, security, and system integration.
• Lead Technical Strategy in Pre-Sales: Partner with Sales and Solutions Engineering to lead late-stage technical discovery, scope complex proofs-of-concept (POCs), and design the technical architecture that secures the win.
• Oversee Data & Model Lifecycle: Guide the ingestion, transformation, and validation of large datasets for agent training and deployment. Implement CI/CD pipelines for seamless model deployment and monitoring.
• Drive Innovation and Best Practices: Stay on the cutting edge of AI/ML advancements. Create technical documentation, architectural blueprints, and best practice guidelines that elevate the entire engineering organization.

• Experience: 7-10 years of overall IT experience, with 5+ years in a hands-on AI/ML implementation or architecture role.
• AI/ML Depth: Deep knowledge of machine learning, deep learning, and NLP frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
• Generative AI Expertise: Proven experience designing and deploying Generative AI solutions, particularly RAG architectures, using tools like LangChain, vector databases (Pinecone, Weaviate), and LLM APIs (OpenAI, Gemini).
• Cloud Proficiency: Hands-on expertise with AI/ML services on a major cloud platform (AWS, GCP, or Azure), including relevant certifications.
• Programming: Strong, hands-on programming skills in Python.

• MLOps: Direct experience with MLOps tools (e.g., MLflow, Kubeflow, SageMaker) and building CI/CD pipelines for machine learning.
• Big Data: Expertise with large-scale data pipelines and tools (e.g., Apache Spark, Kafka).
• Enterprise Architecture: Strong background in designing secure, scalable solutions that integrate with a variety of cloud and on-premise services.
• Consulting Mindset: Experience mentoring engineers and a proven ability to articulate complex technical concepts to diverse audiences, including non-technical stakeholders.

Supervity is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law.

‍

Supervity is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at hr@supervity.ai.