DoseSpot

AI Software Architect / Developer

DoseSpot

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $178,200 - $245,000 per year

Job Level

SeniorLead

Tech Stack

AWSAzureCloudDockerJavaKubernetesMicroservices.NETNoSQL

About the role

  • Serve as a cross-functional AI thought partner, driving the strategic roadmap in partnership with Product, Engineering, and Executive leadership. Align AI innovation with company-level objectives and outcomes.
  • Lead technical and strategic evaluation of AI opportunities, framing and executing POCs/POTs with clear business cases, conceptual models, and measurable impact
  • Set technical vision and architectural guardrails for AI/GenAI systems, ensuring alignment with scalability, compliance, and long-term platform strategy.
  • engineering teams to adopt AI-enhanced workflows. Provide architectural leadership and mentorship to embed AI best practices.
  • Act as principal-level SME, architecting AI/ML adoption across product teams. Shape internal standards, advise on build vs. buy decisions, and mentor senior developers.
  • Act as subject matter expert enabling multiple engineering teams to adopt AI-enhanced workflows. Provide architectural leadership and mentorship to embed AI best practices.
  • Lead competitive AI landscape scanning, synthesizing emerging research and tooling into actionable guidance for engineering leadership and product strategy
  • Lead technical discussions and make critical architectural decisions.
  • Ensure adherence to SOLID principles, design patterns, microservices architecture, and domain-driven design (DDD).
  • Develop proof-of-concepts to evaluate new technologies and frameworks.
  • Drive best practices in CI/CD, DevOps, and cloud deployment strategies.
  • Guide development teams in adopting modern AI assisted development technologies

Requirements

  • At least 12 years of software development experience (.NET/C# or JAVA) with a strong focus on architecture
  • 2+ years hands-on experience building applications using LLMs (GPT, Claude, LLaMA etc) or GenAI frameworks (LangChain, LlamaIndex etc) and using RAG techniques to enhance LLMs.
  • Proven track record building and scaling high-transaction SaaS platforms, ensuring performance, reliability, and security in mission-critical environments.
  • Demonstrable experience using proprietary data for fine tuning, prompt orchestrations, search, retraining and monitoring model outputs.
  • Demonstrable experience in evaluating mode performance using thorough quantitative and qualitative benchmarks, including hallucination detection, latency and prompt quality.
  • Experience developing AI assisted solutions in the Healthcare industry along with awareness of ethical AI practices within healthcare industry, including data privacy and de-identification is a strong plus.
  • Solid understanding of RESTful APIs, backend development in a high transaction volume application.
  • Proficiency in cloud platforms (Azure or AWS) and containerization (Docker/Kubernetes).
  • Experience with microservices architecture, event-driven design, and serverless computing.
  • Expertise in database design with Relational and NoSQL Databases.
  • Hands-on experience with Azure DevOps, Git, and CI/CD pipelines.
  • Strong understanding of security best practices, authentication mechanisms (OAuth, JWT, OpenID Connect).
  • Deep expertise in enterprise performance architecture, caching layers, latency optimization, and failover strategies for mission-critical systems.
  • Led Agile at scale (SAFe, or squad model); partnered with PM/TPMs to align sprint planning to strategic tech investments
  • Excellent executive communication skills, with the ability to influence diverse stakeholders and translate advanced technical topics into business outcomes.
  • Proven ability to collaborate across cross-functional teams including Engineering, Product, Cloud Ops, and Executive stakeholders to drive AI-enabled transformation; experience in leading through influence, creating alignment across teams without direct authority by building credibility, communicating vision, and unblocking friction points.
  • Adept at influencing architectural and product decisions at the leadership level by framing trade-offs, navigating ambiguity, and aligning technical direction with organizational priorities, particularly at the intersection of technical complexity and strategic business impact.